1456 Generative Ai Jobs - Page 42

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Assistant Vice President - Record to Report- GPO In this role, GPO lead is responsible for directing and executing GPO roadmap that solves the business problems/opportunities of the key customer(s) in the F&A domain through the usage of methodologies like Lean, Six Sigma, Business process re-engineering, and by combining technology solutions like Automation Anywhere, Blue Prism, etc. In this role, you would be responsible for the effective delivery of planned Digital projects, RPA bots, AIML projects and Six Sigma projects working with cross-functional global leads including the digital delivery team, and client leadership successfully. This role may involve directly managing the account or reporting to an account manager, but the responsibility of planning and delivering the GPO strategy would be with the lead role. Responsibilities . Thorough Continuous Improvement, delivery on committed productivity, productivity improvement in account and Bad Bench reduction . Champion the implementation and adoption of standard Global Processes . Support and deliver operational excellence and automation and implement best practices and drive efficiency and standardization as approved by . Assess new Laws, policies and practices, organization changes and the impact on the Global Processes and communicate such changes and impact to client . Lead and be responsible for all trainings and knowledge transfer relating to the GPO Services . Create Transformation Road Map and deliver projects aligned with client . Deploy RPA, Macros, Visualizations dashboards and Lean Six sigma, COE projects for mitigating process issues and improving Operational efficiencies identified across towers . Design, implement, test and complete all In-Scope CI Projects . Engage and leverage lean six sigma practices and processes . Support Operations to meet key transformation objectives of client and deliver required business value, productivity . Identify and log Issues and Incidents, perform Root Cause Analysis and determine root causes that are leading to Issues recommend process and System improvements and resolve Issues and Incidents . Manage client relationships and deliver transformation roadmap . Lead large teams for transformation resources to deliver program . Drive deployment of AIML tools in operations to improve process performance, metric improvement and deliver business value Qualifications we seek in you! Minimum Qualifications . Experience in Oracle Fusion, Tririga, Blackline, Service Now etc. or similar technology and technology deployments . Experience in driving RPA program and deploying RPA across platforms . Extensive experience in the Record to Report domain should have led transformation across all sub-processes like Manual Journals, Fixed Asset, Reconciliation etc. . Experience in driving continuous improvement using Lean, Six Sigma Methodology . Experience in managing client discussion and driving large transformation programs . Experience in deploying AIML or Generative AI solution and driving analytics programs . Project Management skills -Strong Influencing skills and clarity of thought on effective project management are required . People Leadership: Ability to coach & mentor people. Ability to effectively influence & motivate others and Ability to work in diverse teams and with multiple stakeholders . Delivers oral and written communications that have clarity and impact . Creates a team environment of accountability and commitment for reaching project goals . Must be able to work in dynamic and tight deadlines to meet the project schedule . Exposure to business metric improvement initiatives like close optimization . Understanding of Defining SLA/KPI and linking it to business metrics . Experienced Process improvement and Automation expert with domain exposure in F&A Preferred Qualifications/ Skills . Lean Six Sigma- GB / BB certification . Exposure to AIML certification would be added advantage . Tenured experience leading transformation Why join Genpact . Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities . Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Assistant Vice President - Record to Report- EPA Enterprise Process Architect is responsible for directing and executing GPO roadmap that solves the business problems/opportunities of the key customer(s) in the F&A domain through the usage of methodologies like Lean, Six Sigma, Business process re-engineering, and by combining technology solutions like Automation Anywhere, Blue Prism, etc. In this role, you would be responsible for the effective delivery of planned Digital projects, RPA bots, AIML projects and Six Sigma projects working with cross-functional global leads including the digital delivery team, and client leadership successfully. This role may involve directly managing the account or reporting to an account manager, but the responsibility of planning and delivering the GPO strategy would be with the lead role. Responsibilities . Thorough Continuous Improvement, delivery on committed productivity, productivity improvement in account and Bad Bench reduction . Champion the implementation and adoption of standard Global Processes . Support and deliver operational excellence and automation and implement best practices and drive efficiency and standardization as approved by . Assess new Laws, policies and practices, organization changes and the impact on the Global Processes and communicate such changes and impact to client . Lead and be responsible for all trainings and knowledge transfer relating to the GPO Services . Create Transformation Road Map and deliver projects aligned with client . Deploy RPA, Macros, Visualization dashboards and Lean Six sigma, COE projects for mitigating process issues and improving Operational efficiencies identified across towers . Design, implement, test and complete all In-Scope CI Projects . Engage and leverage lean six sigma practices and processes . Support Operations to meet key transformation objectives of client and deliver required business value, productivity . Identify and log Issues and Incidents, perform Root Cause Analysis and determine root causes that are leading to Issues recommend process and System improvements and resolve Issues and Incidents . Manage client relationship and deliver transformation roadmap . Lead large teams for transformation resources to deliver program . Drive deployment of AIML tools in operations to improve process performance, metric improvement and deliver business value Qualifications we seek in you! Minimum Qualifications / Skills . Experience in Oracle Fusion, Tririga, Blackline, Service Now etc. or similar technology and . technology deployments . Experience in driving RPA program and deploying RPA across platforms . Extensive experience in the Record to Report domain should have led transformation across all . sub-processes like Manual Journals, Fixed Asset, Reconciliation etc. . Experience in driving continuous improvement using Lean, Six Sigma Methodology . Experience in managing client discussion and driving large transformation programs . Experience in deploying AIML or Generative AI solution and driving analytics programs . Project Management skills -Strong Influencing skills and clarity of thought on effective project . management are required . People Leadership: Ability to coach & mentor people. Ability to effectively influence & motivate . others and Ability to work in diverse teams and with multiple stakeholders . Delivers oral and written communications that have clarity and impact . Creates a team environment of accountability and commitment for reaching project goals . Must be able to work in dynamic and tight deadlines to meet the project schedule . Exposure to business metric improvement initiatives like close optimization . Understanding of Defining SLA/KPI and linking it to business metrics . Experienced Process improvement and Automation expert with domain exposure in F&A Preferred Qualifications/ Skills . Lean Six Sigma- GB / BB certification . Exposure to AIML certification would be added advantage . Tenured experience leading transformation Why join Genpact . Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities . Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Title : Lead Data Scientist/ML Engineer (6+ years & above) Required Technical Skillset : Language : Python , PySpark Framework : Django, Flask, Fastapi, Libraries : NumPy, Pandas, Matplotlib, SciPy, Scikit-learn - DataFrame, Numpy, boto3 Database : Relational Database(Postgres), NoSQL Database (MongoDB), Good to have -SQL Cloud : AWS cloud platforms Other Tools : Jenkins, Bitbucket, JIRA, Confluence Good to Have: agentic ai, ai agent A machine learning engineer is responsible for designing, implementing, and maintaining machine learning systems and algorithms that allow computers to learn from and make predictions or decisions based on data. The role typically involves working with data scientists and software engineers to build and deploy machine learning models in a variety of applications such as natural language processing, computer vision, and recommendation systems. The key responsibilities of a machine learning engineer includes : - Collecting and preprocessing large volumes of data, cleaning it up, and transforming it into a format that can be used by machine learning models. - Model building which includes Designing and building machine learning models and algorithms using techniques such as supervised and unsupervised learning, deep learning, and reinforcement learning. - Evaluating the model performance of machine learning models using metrics such as accuracy, precision, recall, and F1 score. - Deploying machine learning models in production environments and integrating them into existing systems using CI/CD Pipelines, AWS Sagemaker - Monitoring the performance of machine learning models and making adjustments as needed to improve their accuracy and efficiency. - Working closely with software engineers, product managers and other stakeholders to ensure that machine learning models meet business requirements and deliver value to the organization. Requirements and Skills : Mathematics and Statistics : - A strong foundation in mathematics and statistics is essential. - They need to be familiar with linear algebra, calculus, probability, and statistics to understand the underlying principles of machine learning algorithms. Programming Skills : - Should be proficient in programming languages such as Python . - The candidate should be able to write efficient, scalable, and maintainable code to develop machine learning models and algorithms. Big Data Technologies : - A machine learning engineer should have experience working with big data technologies such as Hadoop, Spark, and NoSQL databases. - They should be familiar with distributed computing and parallel processing to handle large data sets. Software Engineering : - A machine learning engineer should have a good understanding of software engineering principles such as version control, testing, and debugging. - They should be able to work with software development tools such as Git, Jenkins, and Docker. Communication and Collaboration : - A machine learning engineer should have good communication and collaboration skills to work effectively with cross-functional teams such as data scientists, software developers, and business stakeholders.

We are looking for a skilled and creative Generative AI Engineer with 2 to 3 years of experience to join our AI/ML team. You will work on designing, fine-tuning, and deploying generative models (text, image, audio, or multi-modal) that power next-gen AI applications across business verticals. This is a hands-on role requiring a solid understanding of deep learning, model training/inference pipelines, and deployment best practices. Key Responsibilities • Build and fine-tune generative models using transformer architectures (e.g., GPT, LLaMA, T5, BERT) and diffusion models (e.g., Stable Diffusion). • Integrate LLMs into production workflows using APIs or custom backends. • Design and implement Retrieval-Augmented Generation (RAG) systems using vector databases like FAISS, Qdrant, or Pinecone. • Optimize prompt engineering and chain-of-thought logic for domain-specific tasks. • Evaluate model outputs for accuracy, relevance, hallucination rate, and latency. • Collaborate with product and engineering teams to turn prototypes into scalable systems. • Contribute to model monitoring, drift detection, and feedback loops for continual improvement. Required Skills • 23 years of experience working with machine learning models, with a focus on generative AI. • Proficient in Python and libraries such as PyTorch, TensorFlow, Transformers (Hugging Face). • Hands-on experience with OpenAI API, LangChain, or LlamaIndex. • Familiarity with vector databases (FAISS, Qdrant, Pinecone) and embedding models. • Strong understanding of LLM behavior, including prompt design, token limits, and context handling. • Experience deploying models using FastAPI, Docker, and cloud platforms (AWS, GCP, or Azure). • Good grasp of model evaluation, explainability, and safety techniques. Preferred Qualifications • Experience with multimodal AI (e.g., text-to-image, text-to-audio). • Exposure to MLOps workflows, CI/CD for ML pipelines. • Contributions to open-source AI projects or research papers. • Knowledge of privacy-preserving AI, RLHF, or federated learning is a plus.

Role Overview Lead the integration of AI technologies into multimedia design processes to produce innovative and impactful content, reinforcing Moving Walls position as a global AdTech leader. Key Responsibilities AI Content Creation : Use AI tools to create high-quality visual, audio, and video content while automating workflows. Brand Integration : Align multimedia outputs with brand guidelines and collaborate on strategic messaging. Marketing Support : Enhance campaigns with AI-generated graphics, videos, animations, and immersive content (e.g., AR/VR). R&D : Stay updated on AI trends, experiment with new technologies, and integrate advancements into production. Collaboration & Training : Work with teams to identify multimedia opportunities and train them on AI tools. Key Performance Indicators (KPIs) Reduced content production time and increased output. Improved engagement metrics (CTR, shares, viewership). Successful introduction of innovative content formats. Consistent brand alignment in all materials. Qualifications Experience : 7+ years in multimedia design with a focus on AI-driven content. Technical Expertise : Proficiency in AI tools (e.g., MidJourney, RunwayML) and multimedia software (Adobe Creative Suite, Figma). Skills : Strong visual storytelling, audience engagement, and project management. Track Record : Proven success integrating AI innovation into creative projects. Tech Stack Generative AI: DALL-E, MidJourney, RunwayML, ChatGPT. Video: Adobe After Effects, Lumen5. Design: Canva Pro AI, Adobe Firefly. Marketing & Analytics: HubSpot, Google Analytics, SEMrush. Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India

Role & responsibilities • Familiarity with Mainframe and Midrange platforms is essential for integrating Gen AI solutions into legacy enterprise systems. Candidate should understand data structures, interfaces, and operational workflows on platforms like IBM Z(Mainframe) and IBM I (Midrange). Experience in modernizing and bridging AI applications with these systems is a strong advantage. masters or PhD in Computer Science, Machine Learning, or related field (or equivalent experience) 5+ years in AI/ML development, with 3+ years focused on generative AI (LLMs, GANs, VAEs, etc.) Proven track record of deploying generative AI solutions in production environments mandatory technical skills: deep expertise in generative architectures (GPT, Transformers, Diffusion Models) Experience with NLP tools (Hugging Face, spaCy) and vector databases (Pinecone, FAISS) mandatory proficiency in Python, PyTorch/TensorFlow, and cloud platforms preferred: knowledge of multimodal AI (text-to-image, video synthesis) experience with reinforcement learning (RLHF) for model alignment preferred familiarity with AI ethics frameworks (e.g., AI Fairness 360) strong analytical and problem-solving skills, excellent communication and collaboration abilities, attention to detail and ability to work independently Interested candidate can share me resume in recruiter.wtr26@walikingtree.in

Responsibilities: Develop and deploy advanced analytics solutions leveraging AI, ML, DL, and Generative AI models. Collaborate with stakeholders to understand business challenges and design data-driven solutions. Build, test, and optimize machine learning pipelines and automation processes using Python. Work with relational and non-relational databases; write efficient SQL queries. Implement asynchronous programming techniques to enhance system performance. Design and develop scalable applications and APIs using frameworks like Django and Flask. Create and integrate REST APIs for seamless data exchange between systems. Deploy and manage analytics solutions in production environments. Troubleshoot and resolve issues in deployment, automation, and analytics workflows. Stay updated with the latest advancements in AI/ML/DL and Generative AI technologies. Requirements: Bachelors/ Masters degree in Computer Science, Data Science, or a related field. 5+ years of hands-on experience in analytics and AI/ML solution development. Proficient in Python and Python-based automation techniques. Solid understanding of AI/ML/DL concepts and familiarity with Generative AI models. Strong experience with SQL and database management (e.g., MySQL, PostgreSQL, MongoDB). Hands-on experience with asynchronous programming in Python. Proficiency with frameworks such as Django and Flask for application development. Experience in deploying machine learning models and applications. Familiarity with REST API development and integration. Strong problem-solving skills and ability to work in a collaborative environment. Preferred Skills: Knowledge of BI Tools such as Qlik & Power BI. Knowledge of cloud platforms (AWS, Azure, GCP) for AI/ML deployment. Experience with containerization tools like Docker and orchestration platforms like Kubernetes. Soft Skills: Strong analytical and critical thinking abilities. Excellent communication and interpersonal skills. Ability to work independently and within cross-functional teams.

Role: Gen AI and ML Eng Exp:3-10 Years Location: Hyderabad/Bangalore NP:Immediate -15 Days(Do Not share more than 15 Days NP Candidates) Required skillsets: Bachelors or masters degree in computer science, Data Science, Engineering, or a related field (PhD preferred). 3+ years of experience in machine learning, deep learning, or AI, with a focus on GenAI. Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or similar. Hands-on experience with large language models (LLMs), generative models, and NLP techniques. Strong understanding of data structures, algorithms, and statistical methods. Experience deploying ML models in production environments (cloud or on-premises). Excellent problem-solving, communication, and collaboration skills. Define and execute the AI/ML strategy in alignment with business goals. Lead the architecture, development, and deployment of state-of-the-art GenAI and ML models, including large language models (LLMs) and generative architectures. Serve as a subject matter expert, advising executive leadership and cross-functional teams on AI/ML opportunities, risks, and best practices. Mentor, coach, and develop junior and mid-level data scientists and engineers. Oversee the design and optimization of robust data pipelines and scalable infrastructure for model training, evaluation, and deployment. Evaluate and integrate emerging technologies, tools, and frameworks to maintain a competitive edge. Represent the organization in external forums, conferences, or industry groups as an AI thought leader. Ensure compliance with ethical, legal, and regulatory standards in AI/ML applications. Must Have:- GenAI and ML Good to Have:- SQL, Databricks Role & responsibilities If Anyone interested please share resume@Rina.nahak@rite.digital

Must have expertise in fine tuning and training models. Must have implemented projects with expertise on Agents, Tools and RAG solutions. Hands-on expertise in integrating LLMs with VectorDB like chromadb, faiss, pinecone is required. Expertise in PEFT, Quantization of models is required. Experience in Tensorflow, Pytorch, Python, Hugging Face, Transformers is a must. Expert in data preparation, analysis and hands, one expertise in Deep Learning model development is preferred. Additional expertise in deploying models in AWS is desired but optional. Skills OpenAI, Gemini, LangChain, Transformers, Hugging Face, Python, Pytorch, Tensorflow, Vectordb(chromadb, faiss, pinecone) Project experience At least 1-2 live implementation of Generative AI driven solution implementation. Extensive experience in implementing chatbots, knowledge search and in NLP.

Use GPT API or Llama to develop custom frameworks for investment management alternate data analysis Use Orchestration tools like N8n for document ingestion Setup on cloud or private using Coreweave Lead Machine Learning and UI Engineers Required Candidate profile 3+ years of development experience in .NET , Python and Azure 3+ years of experience in Data Science along with hands on GenAI and LLMs Experience with VectorDB, documentation ingestion workflows etc.

Strong Communication Skills Exceptional written and verbal communication skills in English. Ability to craft clear, concise, and impactful messages. Experience using communication formats such as video, newsletters, social media posts, intranet articles, and leadership communications. Project Leadership Skills Proven ability to work independently and drive projects from concept to execution. Strong organizational skills to juggle multiple tasks, stakeholders, and deadlines simultaneously. High attention to detail, ensuring quality and accuracy at every step. Proficiency in GenAI Tools Practical experience (or strong eagerness to develop expertise) using Generative AI platforms to improve communication output. Ability to assess when and how to leverage GenAI to speed up content creation without compromising quality. Openness to learning new AI tools and exploring their application in corporate communications. Collaborative Team Player Ability to build relationships and work effectively across diverse cultures and matrix structures. Positive attitude, strong interpersonal skills, and a team-oriented mindset. Creativity & Innovation Bring fresh, creative ideas for communication practices, storytelling formats, and employee engagement. Ability to transform traditional communications into exciting, modern experiences. Analytical mindset with the ability to interpret communication metrics and feedback. Drive continuous improvement through learnings and innovation. Actively look for ways to streamline processes and enhance communications. Ability to thrive under pressure, adapt to change, and embrace constructive feedback as a path to growth. Develop and execute communication strategies targeting a global audience across multiple channels. Serve as a trusted communications advisor to internal stakeholders, understanding their goals and translating them into effective communication plans. Collaborate with external vendors (designers, video producers, advertising agencies) to deliver high-quality communication assets. Ensure seamless execution of communication campaigns to enhance the overall employee experience. Apply data-driven insights to continuously improve campaign effectiveness. Content Creation & Writing Craft clear, compelling, and engaging messages tailored to different stakeholders, channels, and audiences. Maintain the right tone, style, and level of detail based on the business context. Conceptualize and script content for videos, newsletters, leadership messages, and event communications. Integrate the use of Generative AI (such as ChatGPT) to draft, brainstorm, refine, and elevate communication deliverables with speed and quality. Weekly Newsletter - The Monday Mail Editing Own and manage the weekly global newsletter, The Monday Mail: Edit and refine submissions to ensure clarity, consistency, brand voice, and engagement. Curate content by collaborating with global stakeholders and identifying key company updates and stories. Use analytics tools to track performance, derive insights, and optimize future editions. Employ GenAI capabilities to assist with content repurposing, headline generation, summary writing, and tone adjustments as needed.

About the Role Machine Learning Operations Engineer (GEN AI ) Location : Bengaluru , Chennai , Hyderabad Preferred Immediate Joiners only Responsibilities Strong GenAI and MLops experience is Mandatory Expertise in machine learning frameworks such as TensorFlow, PyTorch and Scikit-learn. Proficient in Deep Learning, Generative AI, cloud platforms like Azure, AWS, GCP for developing and deploying AI/ML models. Familiarity with Azure services and infrastructure as code tools like Terraform and ARM templates. Experience with cross-functional teams in agile environments. Work intently with data scientists, product managers and cross-functional teams to meet business needs. Designing, Developing, Implementing AI models and algorithms with a focus on Generative AI, Machine learning and NLP. Developing and deploying cloud-native applications using Azure services like Azure Functions, Azure ML, Amazon Sage Maker, App Service, Storage and Cosmos DB. Staying updated with the latest AI like Gen AI, machine learning, cloud technologies and applying them to improve processes. Engaging in code and design reviews to collaborate in agile development environments.

Role & responsibilities Role Overview We are looking for a skilled and proactive Full Stack Engineer to join our AI Engineering team. You will play a pivotal role in designing, developing, and scaling AI-driven web applications and platforms. This role is ideal for engineers who are passionate about blending full stack development skills with the emerging world of AI and machine learning, and who thrive in cross-functional, fast-paced environments. Key Responsibilities Develop and maintain scalable web applications and APIs using Python (FastAPI, Flask, Django) and modern frontend frameworks ( React.js, Angular.js ). Build intuitive, responsive UIs using JavaScript/TypeScript , CSS3 , Bootstrap , and Material UI for AI-powered products. Collaborate closely with product teams to deliver GenAI/RAG-based solutions . Design backend services for: Data pipelines ( Azure Data Factory , Data Lake , Delta Lake ) Model inference Embedding and metadata storage (SQL, NoSQL, Vector DBs ) Optimize application performance for AI inference and data-intensive workloads . Integrate third-party APIs, model-hosting platforms ( OpenAI , Azure ML , AWS SageMaker ), and vector databases . Implement robust CI/CD pipelines using Azure DevOps , GitHub Actions , or Jenkins . Participate in architectural reviews and contribute to design best practices across the engineering organization. Required Skills & Experience 46 years of professional full-stack engineering experience. Bachelor's degree in Computer Science, Engineering, or related technical field (BE/BTech/MCA) Strong Python development skills, particularly with FastAPI , Flask , or Django . Experience with data processing using Pandas . Proficient in JavaScript/TypeScript with at least one modern frontend framework ( React , Angular ). Solid understanding of RESTful and GraphQL API design. Experience with at least one cloud platform: Azure : Functions, App Service, AI Search, Service Bus, AI Foundry AWS : Lambda, S3, SageMaker, EC2 Hands-on experience building GenAI applications using RAG and agent frameworks . Database proficiency with: Relational databases: PostgreSQL, SQL Server NoSQL databases: MongoDB, DynamoDB Vector stores for embedding retrieval Familiarity with LLM orchestration tools : LangChain, AutoGen, LangGraph, Crew AI, A2A, MCP Understanding of Responsible AI practices and working knowledge of LLM providers (OpenAI, Anthropic, Google PaLM, AWS Bedrock) Good to Have Skills DevOps & Infrastructure : Terraform, Kubernetes, Docker, Jenkins MLOps capabilities : model versioning, inference monitoring, automated retraining Security experience with OpenID Connect , OAuth2 , JWT Deep experience with data platforms: Databricks , Microsoft Fabric Prior experience in AI/ML R&D or working within cross-functional product teams Soft Skills & Team Expectations Effective communication and documentation skills; ability to clearly articulate technical concepts to both technical and non-technical audiences. Demonstrated ability to work independently as well as collaboratively in a fast-paced environment. A builder's mindset with a powerful desire to innovate, automate, and scale . Comfortable in an agile, iterative development environment. Willingness to mentor junior engineers and contribute to team knowledge growth. Proactive in identifying tech stack improvements, security enhancements, and performance bottlenecks. Preferred Certifications (at least two are preferred) Cloud Certifications (Azure, AWS, GCP) – e.g., Azure DevOps Engineer , AWS Certified ML Specialist , GCP Professional ML Engineer Docker/Kubernetes/Cloud Native certifications (CKAD, CKA, etc.) Why Join PwC CTIO? Work at the cutting edge of AI engineering , deploying real solutions at production scale. Collaborate with visionary AI researchers , engineers, and product leaders to redefine what is possible. Be part of a team that values both rapid experimentation and engineering excellence . Gain exposure to LLMOps and GenAI infrastructure at an enterprise scale. Join a culture that encourages continuous learning, bold thinking , and inclusive innovation . Shift:11am-8pm

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Assistant Vice President - Record to Report- GPO In this role, GPO lead is responsible for directing and executing GPO roadmap that solves the business problems/opportunities of the key customer(s) in the F&A domain through the usage of methodologies like Lean, Six Sigma, Business process re-engineering, and by combining technology solutions like Automation Anywhere, Blue Prism, etc. In this role, you would be responsible for the effective delivery of planned Digital projects, RPA bots, AIML projects and Six Sigma projects working with cross-functional global leads including the digital delivery team, and client leadership successfully. This role may involve directly managing the account or reporting to an account manager, but the responsibility of planning and delivering the GPO strategy would be with the lead role. Responsibilities . Thorough Continuous Improvement, delivery on committed productivity, productivity improvement in account and Bad Bench reduction . Champion the implementation and adoption of standard Global Processes . Support and deliver operational excellence and automation and implement best practices and drive efficiency and standardization as approved by . Assess new Laws, policies and practices, organization changes and the impact on the Global Processes and communicate such changes and impact to client . Lead and be responsible for all trainings and knowledge transfer relating to the GPO Services . Create Transformation Road Map and deliver projects aligned with client . Deploy RPA, Macros, Visualizations dashboards and Lean Six sigma, COE projects for mitigating process issues and improving Operational efficiencies identified across towers . Design, implement, test and complete all In-Scope CI Projects . Engage and leverage lean six sigma practices and processes . Support Operations to meet key transformation objectives of client and deliver required business value, productivity . Identify and log Issues and Incidents, perform Root Cause Analysis and determine root causes that are leading to Issues recommend process and System improvements and resolve Issues and Incidents . Manage client relationships and deliver transformation roadmap . Lead large teams for transformation resources to deliver program . Drive deployment of AIML tools in operations to improve process performance, metric improvement and deliver business value Qualifications we seek in you! Minimum Qualifications . Experience in Oracle Fusion, Tririga, Blackline, Service Now etc. or similar technology and technology deployments . Experience in driving RPA program and deploying RPA across platforms . Extensive experience in the Record to Report domain should have led transformation across all sub-processes like Manual Journals, Fixed Asset, Reconciliation etc. . Experience in driving continuous improvement using Lean, Six Sigma Methodology . Experience in managing client discussion and driving large transformation programs . Experience in deploying AIML or Generative AI solution and driving analytics programs . Project Management skills -Strong Influencing skills and clarity of thought on effective project management are required . People Leadership: Ability to coach & mentor people. Ability to effectively influence & motivate others and Ability to work in diverse teams and with multiple stakeholders . Delivers oral and written communications that have clarity and impact . Creates a team environment of accountability and commitment for reaching project goals . Must be able to work in dynamic and tight deadlines to meet the project schedule . Exposure to business metric improvement initiatives like close optimization . Understanding of Defining SLA/KPI and linking it to business metrics . Experienced Process improvement and Automation expert with domain exposure in F&A Preferred Qualifications/ Skills . Lean Six Sigma- GB / BB certification . Exposure to AIML certification would be added advantage . Tenured experience leading transformation Why join Genpact . Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities . Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Role Overview We are seeking a highly skilled AI Engineer with 8-12 years of experience to lead the development of Generative AI (GenAI) and Machine learning solutions for internal projects. This role requires a self-driven leader with exceptional communication, strategic thinking, and expertise in data analytics and visualization to deliver innovative GenAI tools tailored to internal team needs while driving cross-functional collaboration. Key Responsibilities - GenAI Development: Design and develop advanced GenAI models (e.g., LLMs, DALL E models) and AI Agents to automate internal tasks and workflows. Exposure to LLMs: Utilize Azure Open AI APIs, experience on models like GPT4o, O3 , llama3 Enhance the existing RAG based application: In depth understanding of stages of RAG - chunking, retrieval etc. - Cloud Deployment: Deploy and scale GenAI solutions on Azure Cloud services (e.g., Azure Function App) for optimal performance. In depth understanding of ML models like linear regression, random forest, decision trees. In depth understanding on clustering and supervised models. - AI Agent Development: Build AI agents using frameworks like LangChain to streamline internal processes and boost efficiency. - Data Analytics: Perform advanced data analytics to preprocess datasets, evaluate model performance, and derive actionable insights for GenAI solutions. - Data Visualization: Create compelling visualizations (e.g., dashboards, charts) to communicate model outputs, performance metrics, and business insights to stakeholders. Stakeholder Collaboration: Partner with departments to gather requirements, align on goals, and present technical solutions and insights effectively to non-technical stakeholders. - Model Optimization: Fine-tune GenAI models for efficiency and accuracy using techniques like prompt engineering, quantization, and RAG (Retrieval-Augmented Generation). LLMOps Best Practices: Implement GenAI-specific MLOps, including CI/CD pipelines (Git, Azure DevOps) - Leadership: Guide cross-functional teams, mentor junior engineers, and drive project execution with strategic vision and ownership. Helicopters, strategic Thinking**: Develop innovative GenAI strategies to address business challenges, leveraging data insights to align solutions with organizational goals. - Self-Driven Execution: Independently lead projects to completion with minimal supervision, proactively resolving challenges and seeking collaboration when needed. - Continuous Learning: Stay ahead of GenAI, analytics, and visualization advancements, self-learning new techniques to enhance project outcomes. Required Skills & Experience - Experience: 8-12 years in AI/ML development, with at least 4 years focused on Generative AI and AI agent frameworks. - Education: BTech/BE in Computer Science, Engineering, or equivalent (Masters or PhD in AI/ML is a plus). - Programming: Expert-level Python proficiency, with deep expertise in GenAI libraries (e.g., LangChain, Hugging Face Transformers, PyTorch, Open AI SDK) and data analytics libraries (e.g., Pandas, NumPy), sk-learn. Mac - Data Analytics: Strong experience in data preprocessing, statistical analysis, and model evaluation to support GenAI development and business insights. - Data Visualization: Proficiency in visualization tools (e.g., Matplotlib, Seaborn, Plotly, Power BI, or Tableau) to create dashboards and reports for stakeholders. - Azure Cloud Expertise: Strong experience with Azure Cloud services (e.g., Azure Function App, Azure ML, serverless) for model training and deployment. - GenAI Methodologies: Deep expertise in LLMs, AI agent frameworks, prompt engineering, and RAG for internal workflow automation. - Deployment: Proficiency in Docker, Kubernetes, and CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for production-grade GenAI systems. - LLMOps: Expertise in GenAI MLOps, including experiment tracking (e.g., Weights & Biases), automated evaluation metrics (e.g., BLEU, ROUGE), and monitoring. Soft Skills: - Communication: Exceptional verbal and written skills to articulate complex GenAI concepts, analytics, and visualizations to technical and non-technical stakeholders. - Strategic Thinking: Ability to align AI solutions with business objectives, using data-driven insights to anticipate challenges and propose long-term strategies. - Problem-Solving: Strong analytical skills with a proactive, self-starter mindset to independently resolve complex issues. - Collaboration: Collaborative mindset to work effectively across departments and engage colleagues for solutions when needed. Preferred Skills - Experience deploying GenAI models in production environments, preferably on Azure Familiarity with multi-agent systems, reinforcement learning, or distributed training (e.g., DeepSpeek). - Knowledge of DevOps practices, including Git, CI/CD, and infrastructure-as-code. Advanced data analytics techniques (e.g., time-series analysis, A/B testing) for GenAI applications. - Experience with interactive visualization frameworks (e.g., Dash, Streamlit) for real-time dashboards. - Contributions to GenAI or data analytics open-source projects or publications in NLP, generative modeling, or data scien

Curious about the role ? Generative AI & NLP Development : Design, develop, and deploy advanced applications and solutions using Generative AI models (e.g., GPT, LLaMA, Mistral) and NLP algorithms to solve business challenges and unlock new opportunities for our clients. Model Customization & Fine-Tuning: Apply state-of-the-art techniques like LoRA, PEFT, and fine-tuning of large language models to adapt solutions to specific use cases, ensuring high relevance and impact. Innovative Problem Solving : Leverage advanced AI methodologies to tackle real-world business problems, providing creative and scalable AI-powered solutions that drive measurable results. Data-Driven Insights: Conduct deep analysis of large datasets, uncovering insights and trends that guide decisionmaking, improve operational efficiencies, and fuel innovation. Cross-Functional Collaboration: Work closely with Consulting, Engineering, and other teams to integrate AI solutions into broader business strategies, ensuring the seamless deployment of AI-powered applications. Client Engagement: Collaborate with clients to understand their unique business needs, provide tailored AI solutions, and educate them on the potential of Generative AI to drive business transformation. What do we expect? Generative AI & NLP Expertise: Extensive experience in developing and deploying Generative AI applications and NLP frameworks, with hands-on knowledge of LLM fine-tuning, model customization, and AI-powered automation. Hands-On Data Science Experience: 6+ years of experience in data science, with a proven ability to build and operationalize machine learning and NLP models in real-world environments. AI Innovation: Deep knowledge of the latest developments in Generative AI and NLP, with a passion for experimenting with cutting-edge research and incorporating it into practical solutions. Problem-Solving Mindset: Strong analytical skills and a solution-oriented approach to applying data science techniques to complex business problems. Communication Skills: Exceptional ability to translate technical AI concepts into business insights and recommendations for non-technical stakeholders.

Role & responsibilities: : Define and own the AI transformation strategy across the enterprise, aligned with business priorities and Group ITs digital roadmap. Identify, prioritize, and drive AI use cases that deliver measurable value across functions (e.g., R&D, supply chain, commercial, operations). Establish governance and standards for responsible AI development and usage (e.g., ethical frameworks, data privacy, model lifecycle management). Lead cross-functional teams to design, pilot, and scale AI solutionspartnering with data scientists, engineers, business analysts, and IT delivery teams. Act as a trusted advisor to senior leaders on AI trends, capabilities, and value potential, translating complex concepts into actionable insights. Develop and mature AI capabilities across the organization, including platform selection, talent development, and operating model evolution. Foster a culture of innovation and experimentation, championing AI literacy and embedding agile, data-driven thinking into the organization. Monitor industry trends and emerging technologies, bringing external perspective to shape internal AI innovation. Preferred candidate profile: Proven experience in leading AI, data science, or digital transformation programs at scale. Strong understanding of AI/ML technologies, enterprise IT environments, and data ecosystems. Demonstrated ability to bridge strategy and execution, with a track record of delivering business outcomes through AI. Excellent stakeholder management and communication skills, especially with non-technical audiences and executive leadership Experience in regulated industries (e.g., life sciences, finance, healthcare) is an advantage. Bachelor's or masters degree in computer science, Data Science, Engineering, or related field. MBA or equivalent business qualification is a plus.

Educational Requirements Bachelor of Engineering Service Line Infosys Quality Engineering Responsibilities Implement Generative AI based solutions using Infosys and Industry standard tools and platforms Implement prompt engineering techniques to evaluate model behavior under various input conditions and refining prompts for better accuracy and desired results. Perform AI assurance to test AI infused applications Work closely with cross-functional teams to ensure prompts align with company objectives and user experience. Identify and report bugs, performance bottlenecks, and safety issues. Stay up-to-date with the latest advancements in Generative AI and testing methodologies. Identify and report bugs, performance bottlenecks, and safety issues. Technical and Professional Requirements: Bachelors degree in computer engineering or equivalent 3-5 years of experience in any of the fields -software development, software testing, Test Automation Proficiency in Python or experience with other automation frameworks used in testing (e.g., Selenium, Playwright, etc.). Experience with cloud platforms like AWS, Azure, or GCP. Experience with prompt engineering and evaluating the performance of large language models (LLMs). Experience in Generative AI based solution implementation Preferred Skills: Technology->Machine Learning->Generative AI Technology->Machine Learning->AI/ML Solution Architecture and Design->generative ai

Build and integrate solutions using LLMs and Generative AI frameworks . Apply prompt engineering techniques to optimize LLM outputs for various use cases. Fine-tune pre-trained models to align with domain-specific requirements. Work with Azure OpenAI for deploying, scaling, and managing LLM workloads. Understand and implement deep learning architectures like CNNs and RNNs as required for multimodal and NLP tasks. Write clean and modular code to support experimentation and productization of AI models. Collaborate with data scientists, engineers, and business teams to convert problem statements into technical solutions. Stay updated with the latest trends and research in LLMs , deep learning , and Generative AI . Strong logical thinking and problem-solving abilities. Proficiency in Python and ML/NLP libraries (e.g., PyTorch, TensorFlow, Hugging Face). Hands-on experience with Generative AI and LLMs (e.g., GPT, LLaMA, Mistral). Knowledge of prompt engineering strategies for improving model interaction. Experience with Azure OpenAI services (deployment, model management). Understanding of deep learning models like CNN , RNN , and attention mechanisms. Exposure to vector databases , LangChain , or RAG pipelines . Experience in model fine-tuning , quantization, or training from scratch. Familiarity with ML workflows, data preprocessing, and evaluation metrics.

About this role: Wells Fargo is seeking a Principal Engineer to drive the design, development, and implementation of Artificial Intelligence (AI) enabled applications aligned to employee-facing lines of business in Enterprise Functions Technology (EFT). The EFT AI team will focus on building intelligent, efficient, and user-centric tools to accelerate the work of users in Finance, Human Resources, Risk, Audit, Legal, Public Affairs, Diverse Segments and EFT Platform Technology. In addition to hands-on development, this role will play a key part in evolving the AI operating model for both horizontal (cross product/platform) and vertical support (product specific). As a key technical contributor, you will collaborate with cross-functional teams to align solutions with the mission of transforming the Wells Fargo employee experience. This role will be a key contributor to shaping AI infrastructure, governance, and automation frameworks, working closely with cross-functional partners in technology, product management, and operations. The horizontal focus of this role will support AI platform scalability, reliability and AI governance, ensuring alignment across EFT, while the vertical focus will support specific applications and their integration within business domains. The successful candidate will have a deep expertise in AI engineering, cloud-based AI deployment, and AI model lifecycle management, along with experience in architecting AI solutions that align with responsible principles and enterprise business objectives. This is a unique opportunity to lead AI engineering efforts while shaping the AI operating model. In this role, you will: Design, develop and optimize Gen AI applications using agentic frameworks and tools Accelerate end to end solution delivery timelines by developing automated data, prompting and evaluation pipelines Streamline the enablement of AI solutions by building solution blueprints, re-usable patterns and identifying process improvements Lead AI engineering efforts that drive the design, development, scalability, and evolution of AI-powered products, ensuring AI adoption. Research and guide engineering efforts to solve complex engineering challenges and balance accuracy, latency and cost Evolve the AI operating model, ensuring seamless integration of AI solutions into business domains while providing horizontal AI governance and infrastructure support. Develop automated AI model monitoring frameworks, enabling continuous model updates, explainability, and performance tracking. Develop and scale AI platforms leveraging Large Language Model (LLM) services, real time analytics, AI automation, and intelligent decision-making. Act as an advisor and collaborate with leadership to integrate AI into existing enterprise systems and cloud platforms to implement innovative and significant business solutions. Drive cross-functional collaboration to define AI roadmaps, infrastructure strategies, and product enhancements, ensuring AI capabilities align with business AI strategies. Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that require vision, creativity, innovation, and advanced analytical and thinking. Maintain knowledge of industry best practices and new technologies and recommend innovations that enhance operations or provide a competitive advantage to the organization. Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership. Responsible for meticulous governance to address the unique risks posed by GenAI. Required Qualifications: 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 7+ years of engineering experience building and supporting large scale customer facing products using modern technologies 3+ years building and delivering products using AI technologies. Desired Qualifications: Strong expertise in AI model development and deployment with a strong background in LLMs, generative AI, and AI-engineering. Deep experience with generative AI models, including model prompting, tuning, and safety best practices. Expertise in solution architecture and applying modular design techniques to agentic workflows Solid grasp of data and error analysis, identifying issues and patterns throughout the AI pipeline Strong expertise in test or eval driven development, ensuring robust and scalable AI software. Experience in backend application software development, with ability to quickly adapt to C#, and Python code bases. Strong understanding of Retrieval-Augmented Generation (RAG), knowledge graphs and agentic workflows. Deep knowledge of AI infrastructure, Generative AI Operations, and enterprise-scale AI adoption strategies. Familiarity with enterprise-scale software systems and their integration within large organizations. Passion for building AI solutions that deliver a seamless, end-user-focused experience. Experience in enterprise AI model lifecycle management, AI compliance, and risk mitigation strategies. Strong understanding of human centered AI design for workplace applications. Excellent collaboration, communication, and problem-solving skills. Job Expectations: Lead projects, teams, and serve as a peer mentor. Be Humble: You're smart yet always interested in learning from others Work Transparently: You always deal in an honest, direct, and transparent way. Take Ownership: You embrace responsibility and find joy in having the answers Learn More: You regularly self-educate and improve your skill set. Show Gratitude: You show appreciation and respect to those you work with.

Job Title: Product Manager AI, Cloud Products & CRM Solutions Location: Noida Experience Level: 3 - 5 years Employment Type: Full-time About the Role We are looking for a dynamic and results-driven Product Manager with hands-on experience in both AI-powered solutions and CRM/enterprise software delivery. You will work directly with founders, engineering teams, and business stakeholders to deliver cloud-native, scalable, and user-centric products. This is an exciting opportunity to be at the forefront of innovation across Generative AI, cloud architecture, and enterprise systems. Key Responsibilities Product Strategy & Lifecycle Own the product lifecycle from ideation to launch and continuous improvement. Translate complex business requirements into detailed specs, wireframes, and user stories. Prioritize features using frameworks such as RICE, MoSCoW, and manage product roadmap. AI & Cloud Product Development Collaborate with tech leads to build Generative AI-powered tools (e.g., chatbots, agents, vector search). Stay updated with trends in LLMs, open-source models (OpenAI, Hugging Face, LangChain), and cloud ecosystems (AWS, Azure, GCP). Ensure product architecture supports scale, security, and performance. CRM / Enterprise Software Delivery Lead CRM or enterprise platform development aligned with business workflows. Manage requirements, sprints, backlog grooming, and QA processes to ensure delivery quality. Align technical and business teams to deliver scalable and robust CRM systems. Agile Project Management Facilitate Agile ceremonies: sprint planning, stand-ups, retrospectives. Track sprint goals, blockers, and progress; ensure timely delivery. Manage stakeholder expectations, sprint backlogs, and milestone reviews. Cross-functional Collaboration Work with UI/UX, engineering, QA, DevOps, and data teams to ensure product-market fit. Bridge communication between business stakeholders and development teams. Ensure cohesive delivery aligning with SDLC, Agile, and DevOps practices. Risk, Budget & Quality Management Identify project risks early and implement mitigation plans. Manage project budgets, timelines, and resource allocation efficiently. Conduct UAT and post-launch analysis to refine the product. Required Skills & Qualifications Must-Have: 3 to 5 years of experience as a Product Manager or Project Manager in AI/Tech/CRM domains. Strong understanding of Generative AI (LLMs, RAG, LangChain, OpenAI, Hugging Face, etc.). Solid grasp of SDLC and Agile methodologies (Scrum, SAFe). Technical familiarity: front-end (React, Flutter), back-end (Node.js, Python, Laravel), cloud (AWS, GCP, Azure), APIs. Strong analytical and wireframing skills (Figma, Miro). Excellent communication, documentation, and stakeholder management. Good-to-Have: Experience in 0-to-1 product development or startup environments. Exposure to DevOps, MLOps, or LLMOps pipelines. Certifications such as PMP, CSM, SAFe Agile, or PRINCE2. Experience using tools like Jira, Notion, Trello, GitHub Projects, Postman. Why Join Us? Work directly with founder on visionary AI products. Be a key decision-maker in shaping the next-gen legal, CRM, or data intelligence platforms. Ownership, autonomy, and opportunity to scale the product globally. Competitive compensation + equity options.

Role & responsibilities Develop, test, and maintain backend services using Python and frameworks such as FastAPI or Flask . Implement and optimize LLM-based applications using models like OpenAI (GPT-4o) , Gemini , LLaMA , etc. Work on RAG implementations , including integration with vector databases and prompt engineering strategies. Design, build, and maintain database connectivity using SQL for infrastructure-level applications. Develop and deploy containerized applications using Docker , Git , GitHub , and integrate with CI/CD pipelines . Deploy and manage applications on cloud platforms ( AWS , Azure , GCP ). Ensure clean code practices including unit testing , error handling , Python best practices , and design patterns . Collaborate with cross-functional teams including Product, Data Science, and DevOps for end-to-end solution delivery. Preferred candidate profile Strong proficiency in Python programming . Familiarity with FastAPI , Flask , or similar web frameworks. Experience with SQL databases and connection management. Hands-on with LLMs and RAG workflows (OpenAI GPT, Gemini, LLaMA, etc.). Understanding of vector databases such as FAISS, Pinecone, or similar. Proficiency with Git , GitHub , and CI/CD pipelines . Experience with Docker for containerization. Exposure to any of the major cloud platforms AWS , Azure , or GCP . Ability to write unit test cases , implement robust error handling , and follow design patterns . Clear understanding of enterprise software development best practices . Someone who have experience working with Banking or Financial Services projects/clients. Immediate Joiner or someone serving notice period.

Total experience 7+ Years. Deep understanding of Generative AI fundamentals and transformer-based architectures. Strong experience in Cloud Architecture (e.g., AWS, Azure, GCP) for deploying scalable AI systems. Proven experience with BERT, GPT, LLaMA, and similar LLMs. Strong hands-on experience in prompt engineering and RAG techniques. Experience in fine-tuning and deploying models using frameworks like Hugging Face Transformers, LangChain, or equivalent. Familiarity with multi-agent AI systems and collaborative model workflows. Proficient in Python and machine learning libraries (e.g., PyTorch, TensorFlow). Strong problem-solving skills and a passion for AI innovation and ethical development. Experience integrating models into enterprise platforms and APIs. Understanding of ML Ops practices and CI/CD pipelines for AI deployment. Background in Natural Language Processing (NLP) and Knowledge Engineering. Excellent communication skills, with the ability to articulate solutions effectively. RESPONSIBILITIES: Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements. Mapping decisions with requirements and be able to translate the same to developers. Identifying different solutions and being able to narrow down the best option that meets the clients requirements. Defining guidelines and benchmarks for NFR considerations during project implementation Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed. Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it Understanding and relating technology integration scenarios and applying these learnings in projects Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken. Carrying out POCs to make sure that suggested design/technologies meet the requirements.

Total experience 7+ Years. Deep understanding of Generative AI fundamentals and transformer-based architectures. Strong experience in Cloud Architecture (e.g., AWS, Azure, GCP) for deploying scalable AI systems. Proven experience with BERT, GPT, LLaMA, and similar LLMs. Strong hands-on experience in prompt engineering and RAG techniques. Experience in fine-tuning and deploying models using frameworks like Hugging Face Transformers, LangChain, or equivalent. Familiarity with multi-agent AI systems and collaborative model workflows. Proficient in Python and machine learning libraries (e.g., PyTorch, TensorFlow). Strong problem-solving skills and a passion for AI innovation and ethical development. Experience integrating models into enterprise platforms and APIs. Understanding of ML Ops practices and CI/CD pipelines for AI deployment. Background in Natural Language Processing (NLP) and Knowledge Engineering. Excellent communication skills, with the ability to articulate solutions effectively. RESPONSIBILITIES: Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements. Mapping decisions with requirements and be able to translate the same to developers. Identifying different solutions and being able to narrow down the best option that meets the clients requirements. Defining guidelines and benchmarks for NFR considerations during project implementation Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed. Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it Understanding and relating technology integration scenarios and applying these learnings in projects Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken. Carrying out POCs to make sure that suggested design/technologies meet the requirements.

Total experience 7+ Years. Deep understanding of Generative AI fundamentals and transformer-based architectures. Strong experience in Cloud Architecture (e.g., AWS, Azure, GCP) for deploying scalable AI systems. Proven experience with BERT, GPT, LLaMA, and similar LLMs. Strong hands-on experience in prompt engineering and RAG techniques. Experience in fine-tuning and deploying models using frameworks like Hugging Face Transformers, LangChain, or equivalent. Familiarity with multi-agent AI systems and collaborative model workflows. Proficient in Python and machine learning libraries (e.g., PyTorch, TensorFlow). Strong problem-solving skills and a passion for AI innovation and ethical development. Experience integrating models into enterprise platforms and APIs. Understanding of ML Ops practices and CI/CD pipelines for AI deployment. Background in Natural Language Processing (NLP) and Knowledge Engineering. Excellent communication skills, with the ability to articulate solutions effectively. RESPONSIBILITIES: Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements. Mapping decisions with requirements and be able to translate the same to developers. Identifying different solutions and being able to narrow down the best option that meets the clients requirements. Defining guidelines and benchmarks for NFR considerations during project implementation Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed. Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it Understanding and relating technology integration scenarios and applying these learnings in projects Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken. Carrying out POCs to make sure that suggested design/technologies meet the requirements.