459 Rag Jobs - Page 18

Role & responsibilities We are seeking a highly skilled and passionate GenAI & Data Science Engineer with 5-6 years of experience in Python development, Generative AI, and Data Science. The ideal candidate will have a strong background in AI agent workflows, LLM fine-tuning, and Retrieval-Augmented Generation (RAG) models. You will play a key role in designing, developing, and deploying cutting-edge AI solutions using frameworks such as Lang Chain, Llama Index, and Hugging Face. This role offers the opportunity to work on transformative AI-driven solutions, leveraging state-of-the-art tools and frameworks to create impactful solutions in real-world applications. Key Responsibilities: Design, develop, and deploy AI solutions with a focus on Generative AI and Data Science. Fine-tune Large Language Models (LLM) and implement Retrieval-Augmented Generation (RAG) models. Collaborate with cross-functional teams to integrate AI models into business workflows. Utilize frameworks such as Lang Chain, Llama Index, and Hugging Face to build scalable AI solutions. Participate in end-to-end AI model development, including data preprocessing, model selection, training, evaluation, and deployment. Continuously monitor and optimize the performance of AI models to ensure they meet business requirements. Work with stakeholders to understand AI requirements and contribute to solution design and architecture. Stay up to date with the latest advancements in AI technologies and industry trends Preferred candidate profile Qualifications Bachelors or Master’s degree in Computer Science, Data Science, AI, or a related field. 3-5 years of professional experience in Python development, AI, and Data Science. Proven experience with Generative AI, including fine-tuning LLMs and working with RAG models. Hands-on experience with frameworks like Lang Chain, Llama Index, and Hugging Face. Strong understanding of machine learning algorithms, deep learning, and natural language processing (NLP). Experience in AI model deployment and scaling in production environments. Technical Skills Programming: Python, including libraries like TensorFlow, PyTorch, Pandas, NumPy, etc. AI/ML Frameworks: Lang Chain, Llama Index, Hugging Face, etc. Machine Learning Algorithms: Supervised and Unsupervised Learning, NLP, Reinforcement Learning. Data Engineering: Data preprocessing, data wrangling, ETL processes. Cloud Platforms: AWS, GCP, Azure (experience with AI tools on cloud platforms). Version Control: Git, GitHub, GitLab. Familiarity with containerization tools like Docker and Kubernetes. Soft Skills Strong problem-solving skills and analytical thinking. Excellent communication and collaboration skills. Ability to work independently and as part of a team. Adaptability to evolving technologies and requirements. Strong attention to detail and high quality of work. Time management and ability to meet deadlines. Work Experience 3-5 years of experience working in AI, Data Science, or a related field. Practical experience in working with Generative AI, LLM fine-tuning, and RAG models. Experience with deployment of AI models in cloud environments. Proven track record delivering AI-driven solutions to solve real business problems. Good to Have Experience with other AI tools and frameworks like OpenAI GPT, DeepPavlov, or similar. Exposure to data integration and API development. Knowledge of advanced topics in NLP, such as transformers and attention mechanisms. Experience with building AI-powered applications or chatbots. Compensation & Benefits Salary: Competitive base salary based on experience and skills. Bonus: Annual performance-based bonus. Benefits: Health insurance, paid time off, work-from-home options, and retirement benefits. Learning & Development: Access to AI and Data Science training, conferences, and certifications. Key Performance Indicators (KPIs) & Key Result Areas (KRAs) KPIs: Timely delivery of AI projects and solutions. Quality and accuracy of fine-tuned AI models. Successful integration of AI solutions into business workflows. Continuous improvement in AI model performance (accuracy, speed, scalability). Stakeholder satisfaction and feedback on AI-driven solutions. Contribution to knowledge sharing and team collaboration. KRAs: AI model development, fine-tuning, and deployment. End-to-end ownership of AI solution delivery. Collaboration with cross-functional teams to define and implement business requirements. Optimization and monitoring of AI solutions in production environments.

Notice Period : Candidates with up to 1-month notice preferred Findability Sciences is looking for a hands-on AI expert with experience in developing and implementing comprehensive predictive and generative AI solutions. This is a core technical role rather than a support-based one. You will lead innovation and delivery across multiple industries. What we are looking for: 3+ years of experience in AI/ML with a Masters or Ph.D. in a relevant field Strong knowledge of Python, SQL, Machine Learning, LLMs, RAG, and Prompt Engineering Experience in predictive modeling, time series forecasting, and generative AI use cases Experience with ML Ops workflows model deployment, monitoring, versioning, and pipeline automation Key Responsibilities: Design and deploy predictive & GenAI solutions for real-world business use cases Build and optimize LLM-based workflows for summarization, retrieval, and Q&A Collaborate with cross-functional teams to define use cases and develop proof-of-concepts Translate business problems into ML/GenAI solutions and deliver outcomes Validate, compare, and optimize models for performance and scalability Apply basic ML Ops practices to ensure smooth deployment and monitoring of models Contribute to reusable pipelines, prompt tuning strategies, and production integration Present actionable insights and models to stakeholders clearly and effectively

Roles and Responsibilities : Must have skills: Python Programming, Machine Learning, Statistical Analysis, Data Science, Generative AI (GPT, DALLE, GANs), Cloud (AWS/Azure/GCP), Model Deployment, API Development, Docker/Kubernetes Good to have skills: PyTorch, TensorFlow, Large-Scale Data Processing, Cloud Integrations, NLP, Computer Vision, Security Best Practices, Performance Optimization, Open-Source Contributions Experience: Minimum 6-12+ years of experience in Data Science, Machine Learning, or related fields with a focus on Generative AI models (LLMs) and API development. Educational Qualification: Bachelor's or Master’s in Computer Science, Data Science, Statistics, Engineering, or related Analytics discipline from a premier institute. Job Summary: Accenture AI is seeking a talented and motivated Generative AI Data Scientist Analyst to join our Banking team. The ideal candidate will leverage their expertise in Generative AI models, Machine Learning, Data Analysis, and Cloud Platforms to develop innovative solutions and enhance AI capabilities. This role will involve collaborating with cross-functional teams to design, develop, and implement generative AI solutions that meet our business needs. Roles & Responsibilities: Collaboration: Work closely with product managers, engineers, and other stakeholders to understand requirements and deliver impactful AI solutions. Model Deployment: Containerize and deploy generative AI models using tools like Docker, Kubernetes, and cloud platforms (e.g., AWS, Azure, Google Cloud). API Development: Design, develop, and deploy robust APIs to expose generative AI models (e.g., GPT, DALLE, Stable Diffusion, GANs) for integration into client systems and applications. Client Collaboration: Work closely with clients to understand their technical requirements and deliver tailored API solutions that meet their business needs. Generative AI Model Integration: Integrate generative AI models into existing workflows, applications, and platforms via APIs. Performance Optimization: Optimize API performance for latency, scalability, and reliability, ensuring seamless user experiences. Data Pipeline Development: Build and maintain data pipelines to support real-time or batch processing for generative AI models. Security and Compliance: Implement security best practices and ensure APIs comply with data privacy and regulatory standards. Documentation: Create comprehensive API documentation, including usage examples, SDKs, and troubleshooting guides. Testing and Monitoring: Develop automated testing frameworks and monitoring systems to ensure API reliability and performance. Stay Updated: Keep up with the latest advancements in generative AI, API development, and cloud technologies to bring innovative solutions to clients. Professional & Technical Skills: Strong proficiency in Python programming and experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Expertise in API Development and deployment, with hands-on experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Ability to build and optimize data pipelines for generative AI models. Knowledge of security best practices and ensuring compliance with regulatory standards. Strong problem-solving, analytical, and creative thinking skills to design and implement innovative solutions. Excellent communication skills, capable of conveying complex technical concepts to diverse audiences. Additional Information: Experience with large-scale data processing and expertise in NLP or computer vision. Contributions to open-source AI/ML projects. Experience with cloud integrations, big data technologies, and performance optimization. Familiarity with security standards and regulatory compliance in AI solutions

Job Description Technical Delivery Manager Saama Technologies Responsibilities: Oversee the end-to-end development and delivery of the Graph RAG system. Manage project timelines, ensuring timely delivery and adherence to milestones. Establish and maintain strong communication with client technical leads, providing regular updates and addressing technical concerns. Offer technical leadership and expertise in Graph Databases (e.g., Neo4j) and LLM-based applications. Collaborate with the team on architectural decisions, ensuring solutions are scalable, robust, and aligned with client requirements. Mitigate technical risks and address challenges proactively. Qualifications: Proven experience in technical project management and delivery, ideally within the AI/ML or data science domain. Strong understanding of Graph Databases and LLM-based systems. Experience with cloud-based development and deployment (AWS, GCP, or Azure). Excellent communication and interpersonal skills, with the ability to bridge the gap between technical and non-technical stakeholders. Ability to work independently and lead a team in a fast-paced environment. Experience with Agile methodologies. Required Skills: Knowledge of Graph Databases (Neo4) - Experience with LLM-based systems - Proficiency in LangChain - API development and cloud deployment expertise - Experience managing engineering teams and Agile methodologies Desired Skills: Familiarity with LangChain and API development. Knowledge of MLOps and CI/CD practices.

About the role PubMatic is seeking Data Analytics-focused Senior Software Engineers with expertise in building and optimizing AI agents, including strong skills in Hadoop, Spark, Scala, Kafka, Spark Streaming, and cloud-based solutions, with proficiency in programming languages such as Scala and Python. You will be responsible for developing advanced AI agents that enhance our data analytics capabilities, enabling our platform to handle complex information retrieval, contextual understanding, and adaptive interactions, ultimately improving our data-driven insights and analytical workflows. What You'll Do Build, design, and implement our highly scalable, fault-tolerant big data platform to process terabytes of data and provide customers with in-depth analytics. Develop backend services using Java, REST APIs, JDBC, and AWS. Build and maintain Big Data pipelines using technologies like Spark, Hadoop, Kafka, and Snowflake. Architect and implement real-time data processing workflows and automation frameworks. Design and develop GenAI-powered agents for analytics, operations, and data enrichment use cases using frameworks like LangChain, LlamaIndex, or custom orchestration systems. Integrate LLMs (e.g., OpenAI, Claude, Mistral) into existing services for query understanding, summarization, and decision support. Manage end-to-end GenAI workflows including prompt engineering, fine-tuning, vector embeddings, and retrieval-augmented generation (RAG). Working closely with cross-functional teams on improving the availability and scalability of large data platforms and the functionality of PubMatic software. Participate in Agile/Scrum processes such as sprint planning, sprint retrospective, backlog grooming, user story management, and work item prioritization. Frequently discuss with product managers about the software features to include in the PubMatic Data Analytics platform. Support customer issues over email or JIRA (bug tracking system), provide updates, and patches to customers to fix the issues. Perform code and design reviews for code implemented by peers or as per the code review process. We'd Love for You to Have Three to six years of coding experience in Java and backend development. Solid computer science fundamentals, including data structure and algorithm design, and creation of architectural specifications. Expertise in developing the Implementation of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews. Hands-on experience with Big Data tools and systems like Scala Spark, Kafka, Hadoop, and Snowflake. Proven expertise in building GenAI applications, including: LLM integration (OpenAI, Anthropic, Cohere, etc.) LangChain, or similar agent orchestration libraries Prompt engineering, embeddings, and retrieval-based generation (RAG) Experience in developing and deploying scalable, production-grade AI or data systems. Ability to lead end-to-end feature development and debug distributed systems. Experience in developing and delivering large-scale big data pipelines, real-time systems & data warehouses would be preferred. Demonstrated ability to achieve stretch goals in a very innovative and fast-paced environment. Demonstrated ability to learn new technologies quickly and independently. Excellent verbal and written communication skills, especially in technical communications. Strong interpersonal skills and a desire to work collaboratively. Qualifications Should have a bachelor's degree in engineering (CS / IT) or equivalent degree from a well-known institute/university. Apply to the link below: https://pubmatic.com/job/?gh_jid=4692032008

Technical Architect - GenAI Job Responsibilities Excellent communication skills and customer management skills 12+ years of deep technical expertise in distributed transactional scale & digital architectures. Experience in Solution Architecture Experience in Java or .NET and related frameworks Experience in GenAI, ChatGPT, LLM, RAG architectures Experience in CoPilot etc Experience in Cloud solutions. Either AWS or Azure or GCP Experience in Microservices and cloud native architectures Role Purpose The purpose of the role is to create exceptional architectural solution design and thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction. Develop architectural solutions for the new deals/ major change requests in existing deals Creates an enterprise-wide architecture that ensures systems are scalable, reliable, and manageable. Provide solutioning of RFPs received from clients and ensure overall design assurance Develop a direction to manage the portfolio of to-be-solutions including systems, shared infrastructure services, applications in order to better match business outcome objectives Analyse technology environment, enterprise specifics, client requirements to set a collaboration solution design framework/ architecture Provide technical leadership to the design, development and implementation of custom solutions through thoughtful use of modern technology Define and understand current state solutions and identify improvements, options & tradeoffs to define target state solutions Clearly articulate, document and sell architectural targets, recommendations and reusable patterns and accordingly propose investment roadmaps Evaluate and recommend solutions to integrate with overall technology ecosystem Works closely with various IT groups to transition tasks, ensure performance and manage issues through to resolution Perform detailed documentation (App view, multiple sections & views) of the architectural design and solution mentioning all the artefacts in detail Validate the solution/ prototype from technology, cost structure and customer differentiation point of view Identify problem areas and perform root cause analysis of architectural design and solutions and provide relevant solutions to the problem Collaborating with sales, program/project, consulting teams to reconcile solutions to architecture Tracks industry and application trends and relates these to planning current and future IT needs Provides technical and strategic input during the project planning phase in the form of technical architectural designs and recommendations Collaborates with all relevant parties in order to review the objectives and constraints of solutions and determine conformance with the Enterprise Architecture. Identifies implementation risks and potential impacts. Enable Delivery Teams by providing optimal delivery solutions/ frameworks Build and maintain relationships with executives, technical leaders, product owners, peer architects and other stakeholders to become a trusted advisor Develops and establishes relevant technical, business process and overall support metrics (KPI/SLA) to drive results Manages multiple projects and accurately reports the status of all major assignments while adhering to all project management standards Identify technical, process, structural risks and prepare a risk mitigation plan for all the projects Ensure quality assurance of all the architecture or design decisions and provides technical mitigation support to the delivery teams Recommend tools for reuse, automation for improved productivity and reduced cycle times Leads the development and maintenance of enterprise framework and related artefacts Develops trust and builds effective working relationships through respectful, collaborative engagement across individual product teams Ensures architecture principles and standards are consistently applied to all the projects Ensure optimal Client Engagement Support pre-sales team while presenting the entire solution design and its principles to the client Negotiate, manage and coordinate with the client teams to ensure all requirements are met and create an impact of solution proposed Demonstrate thought leadership with strong technical capability in front of the client to win the confidence and act as a trusted advisor Competency Building and Branding Ensure completion of necessary trainings and certifications Develop Proof of Concepts (POCs),case studies, demos etc. for new growth areas based on market and customer research Develop and present a point of view of Wipro on solution design and architect by writing white papers, blogs etc. Attain market referencability and recognition through highest analyst rankings, client testimonials and partner credits Be the voice of Wipros Thought Leadership by speaking in forums (internal and external) Mentor developers, designers and Junior architects in the project for their further career development and enhancement Contribute to the architecture practice by conducting selection interviews etc Team Management Resourcing Anticipating new talent requirements as per the market/ industry trends or client requirements Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Stakeholder Interaction Stakeholder Type Stakeholder Identification Purpose of Interaction Internal Delivery teamsReview of architectural process deployment in engagements, escalation management, issue resolution Pre-sales teamFor solutioning and architectural design purposePractice teamsTo understand the different solution portfoliosHolmes engineering and roll outFor automation purposeTalent Transformation Team, Competency GroupPlan and support delivery of Technical Trainings, knowledge sharing HRBPFor hiring and managing resourcesFinanceRevenue / budgetsTalent acquisition teamRecruitment External Vendors/ PartnersFor strategic alignment and partnerships, training Industry forums Best practices, market intelligence, knowledge sharing Display Lists the competencies required to perform this role effectively Functional Competencies/ Skill Domain/Industry Knowledge - Awareness and knowledge of broad economic, demographic, technological and global trends within own ecosystem - Expert Market Intelligence - Deep specialized understanding of the ecosystem practice, overall market & competition and nuances of delivery in that domain - Master Systems Thinking - Understanding of the Wipro system (interrelatedness, interdependencies and boundaries) and perform problem solving in a complex environment - Expert Leveraging Technology - In-depth knowledge of and mastery over ecosystem technology that commands expert authority respect - Master Asset reusability - ability to re-use the assets to ensure scalability and optimization - Expert Technical knowledge - architecture design principles, framework and documentation - Expert Competency Levels Foundation Knowledgeable about the competency requirements. Demonstrates (in parts) frequently with minimal support and guidance. Competent Consistently demonstrates the full range of the competency without guidance. Extends the competency to difficult and unknown situations as well. Expert Applies the competency in all situations and is serves as a guide to others as well. Master Coaches others and builds organizational capability in the competency area. Serves as a key resource for that competency and is recognised within the entire organization. Behavioral Competencies Strategic perspective Technology Acumen Innovation Managing Complexity Client centricity Execution excellence Change agility Passion for results Nurturing people Executive presence Deliver No. Performance Parameter Measure 1. Support sales team to create wins % of proposals with Quality Index >7, timely support of the proposals, identifying opportunities/ leads to sell services within/ outside account (lead generation), no. of proposals led 2. Delivery support CSAT, delivery as per cost, quality and timelines, Identify and develop resuable components, utilization %, Recommend tools for reuse, automation for improved productivity and reduced cycle times 3. Capability development % trainings and certifications completed, increase in ACE certifications, thought leadership content developed (white papers, Wipro PoVs) 4. Team Management Team attrition %, Employee satisfaction score

Hiring an AI-focused developer with expertise in Node.js, API integration (Azure OpenAI, RAG, parameter tuning), and AI pipeline optimization. Bonus: MCP knowledge & experience with image analysis. AI Developer Required Candidate profile AI Developer with 2+ years' experience in Node.js, Azure OpenAI, RAG, API integration, and AI pipelines. Bonus: MCP knowledge & image analysis (OpenAI/Anthropic).

Job Description Requirement Name / Title GenAI Developer Work Location Chennai/ Bangalore/Pune/Kolkata Shift General Shift Mandatory Skills Gen AI, LLM, RAG, Lang chain, Mistral,Llama, Vector DB, Azure/GCP/ Lambda, Python, Tensorflow, Pytorch Preferred Skills GPT-4, NumPy, Pandas, Keras, Databricks, Pinecone/Chroma/Weaviate, Scale/Labelbox, Job Description / Roles & Responsibilities (in Detail) We are looking for a good Python Developer with Knowledge of Machine learning and deep learning framework. • Take care of entire prompt life cycle like prompt design, prompt template creation, prompt tuning/optimization for various GenAI base models • Design and develop prompts suiting project needs • Stakeholder management across business and domains as required for the projects • Evaluating base models and benchmarking performance • Implement prompt guardrails to prevent attacks like prompt injection, jailbreaking and prompt leaking • Develop, deploy and maintain auto prompt solutions • Design and implement minimum design standards for every use case involving prompt engineering • You will be responsible for training the machine learning and deep learning model. • Writing reusable, testable, and efficient code using Python • Design and implementation of low-latency, high-availability, and performant applications • Implementation of security and data protection • Integration of data storage solutions and API Gateways • Production change deployment and related support If you're interested or know someone who fits this role, feel free to reach out. WhatsApp: 9871530393 Email: shweta.gupta@sspearhead.com Warm Regards SHWETA GUPTA || Senior Recruitment Specialist Spearhead Professional Services Call/ WhatsApp: 9871530393 LinkedIn Profile: shwetagupta1810

About the Role We are looking for an experienced and visionary Generative AI Architect with 8-12 years of experience in AI/ML, including hands-on work with LLMs (Large Language Models) and Generative AI solutions . In this strategic technical leadership role, you will be responsible for designing and overseeing the development of advanced GenAI platforms and solutions that transform business operations and customer experiences. As the GenAI Architect, you will work closely with data scientists, ML engineers, product teams, and stakeholders to conceptualize, prototype, and scale generative AI use cases across the organization or client engagements. Key Responsibilities GenAI Solution Architecture & Design Lead the design and development of scalable GenAI solutions leveraging LLMs , diffusion models , and multimodal architectures . Architect end-to-end pipelines involving prompt engineering , vector databases , retrieval-augmented generation (RAG) , and LLM fine-tuning . Select and integrate foundational models (e.g., GPT, Claude, LLaMA, Mistral ) based on business needs and technical constraints. Technical Strategy & Leadership Define GenAI architecture blueprints, best practices, and reusable components for rapid development and experimentation. Guide teams on model evaluation, inference optimization , and cost-effective scaling strategies . Stay current on the rapidly evolving GenAI landscape and assess emerging tools, APIs, and frameworks. Collaboration & Delivery Work with product owners, business leaders, and data teams to identify high-impact GenAI use cases across domains like customer support, content generation, document understanding, and code generation. Support PoCs, pilots, and production deployments of GenAI models in secure, compliant environments. Collaborate with MLOps and cloud teams to enable continuous delivery, monitoring, and governance of GenAI systems. Required Qualifications & Experience Education: Bachelor's or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related technical field . PhD is a plus. Experience: 12–15 years in AI/ML and software engineering, with 3+ years focused on Generative AI and LLM-based architectures . Core Skills Deep expertise in machine learning , natural language processing (NLP) , and deep learning architectures . Hands-on experience with LLMs, transformers, fine-tuning techniques (LoRA, PEFT) , and prompt engineering . Proficient in Python , with libraries/frameworks such as Hugging Face Transformers, LangChain, OpenAI API, PyTorch, TensorFlow . Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and RAG pipelines . Strong understanding of cloud-native AI architectures (AWS/GCP/Azure), containerization (Docker/Kubernetes), and API integration. Architectural & Leadership Skills Proven ability to design and deliver scalable, secure, and efficient GenAI systems . Strong communication skills for cross-functional collaboration and stakeholder engagement. Ability to mentor engineering teams and drive innovation across the AI/ML ecosystem. Nice-to-Have Experience with multimodal models (text + image/audio/video). Knowledge of AI governance, ethical AI, and compliance frameworks . Familiarity with MLOps practices for GenAI , including model versioning, drift detection, and performance monitoring.

Job Title: Executive Human Resource Business Partner (HRBP) Location: Gurgaon Company: IGT Solutions Pvt. Ltd. Industry: IT & BPM – Travel, Transportation, and Hospitality Domain Company Overview: IGT Solutions Pvt. Ltd. is a global leader in IT and Business Process Management (BPM) services, dedicated to delivering innovation and operational excellence across the Travel, Transportation, and Hospitality sectors. With over 10,000+ travel industry experts and 15 state-of-the-art delivery centers worldwide, IGT offers comprehensive solutions in Application Development, Mobility, Testing, Analytics, Contact Center Services, Back Office Operations, and Consulting. IGT is committed to a diverse and inclusive workplace and provides equal employment opportunities without regard to age, gender, race, religion, disability, or other protected statuses. Job Summary: We are seeking a dynamic and experienced Executive – HR Business Partner (HRBP) to join our team in Gurgaon . This role will lead HR operations for the assigned vertical/process, support business functions, drive employee engagement and retention initiatives, and ensure policy compliance. Key Responsibilities: Employee Relations: Address and resolve employee queries and concerns efficiently; track and report resolution Turnaround Time (TAT). Compliance & Policy Adherence: Enforce labor laws, company discipline, and the Code of Conduct. Attrition Management: Maintain attrition at or below 5%. Employee Engagement: Lead engagement activities, facilitate action planning, record meeting outcomes, and ensure timely follow-ups. Performance Management: Ensure timely KRA sign-offs for new joiners and during internal movements; monitor half-yearly and annual appraisals. Training Compliance: Track training plan adherence for the assigned vertical/process. Exit Management: Conduct exit interviews, analyze survey data, and present actionable insights and trends. Retention Strategies: Implement effective strategies to enhance employee retention and workplace satisfaction. Branding & Market Intelligence: Support employer branding and monitor industry HR best practices. Policy Compliance: Ensure adherence to internal policies including Security, Privacy, Zero Tolerance, Disciplinary, and Learning Agreements. Qualifications: Education: Graduate in any field (preferably with a degree in Psychology, Industrial Relations, or Human Resource Management). Experience: Proven experience in HR Generalist or Specialist roles, especially in labor relations and employee engagement in a BPO/Call Center environment. Skills & Competencies: Proficiency in MS Office tools (Excel, PowerPoint, Word) Strong analytical and problem-solving skills Basic understanding of labor laws and HR practices Ability to multitask and manage deadlines Excellent verbal and written communication skills Strong interpersonal and conflict-resolution abilities Additional Information: Work Environment: Onsite role (Gurgaon office) Work Schedule: Flexibility to work in rotational shifts or 24/7 schedules is mandatory Why Join IGT Solutions? Become part of a global leader that drives meaningful transformation in the travel and hospitality domain. At IGT, you’ll have the opportunity to shape HR practices, contribute to a culture of excellence, and grow your career in a dynamic, people-first environment.

You'll be Responsible for: Design, develop and implement cutting-edge AI/ML solutions, including Large Language Models (LLMs) and Generative AI applications Lead projects end-to-end while mentoring team members in AI-ML, including traditional ML and emerging AI technologies Drive innovation in AI agent development and orchestration for automated decision-making systems Establish best practices for responsible AI development and deployment What you'd have: AI-ML Engineer or Data Scientist with 3 11 years of relevant experience Strong expertise in modern AI frameworks and tools: ML/DL frameworks (TensorFlow, PyTorch, Keras, Sklearn) LLM frameworks (LangChain, LlamaIndex, CrewAI, AutoGen) Vector databases (Pinecone, Weaviate, ChromaDB) – Good To Have Hands-on experience with: Generative AI and foundation models Prompt engineering and LLM fine-tuning AI agent development and orchestration RAG (Retrieval-Augmented Generation) systems Proven experience in data preparation, including: Advanced data preprocessing techniques Feature engineering Data quality assessment and improvement Proficiency in data exploration tools (Pandas, Numpy, Polars) Strong programming skills in Python; R is a plus Deep understanding of: Statistics and probability ML/DL algorithms AI governance and responsible AI practices Experience with: Large-scale data processing Model deployment and MLOps Cost optimization for AI systems Track record of 3-5 successful AI/ML projects in production Excellent communication skills and team leadership ability Continuous learning mindset for emerging AI technologies Skills: Statistics and Mathematics Classical Machine Learning Deep Learning and Neural Networks Generative AI and LLMs Agentic AI Development MLOps and Production Engineering Data Engineering Model Optimization and Tuning AI Governance and Ethics Team Leadership Why join us? Impactful Work: Drive innovation in AI technologies while safeguarding Tanla's assets, data, and reputation Growth Opportunities: Be part of a rapidly growing company in the telecom and CPaaS space, with clear paths for professional advancement Innovative Environment: Work with a world-class team on cutting-edge AI technologies in a challenging and collaborative environment Research Opportunities: Contribute to the advancement of GenAI and Agentic AI technologies Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. www.tanla.com

Role & responsibilities esponsibilities 1Design develop test and implement AI and ML models using the latest technologies and frameworks 2Analyze and interpret complex data to identify trends patterns and insights 3Work with AI lead to understand business objectives and requirements and develop solutions to solve complex problems 4Maintain uptodate knowledge of latest AIML trends techniques and technologies 5Collaborate with data engineers to build data and model pipelines 6Conduct research and implement new methodologies in AI and ML ESSENTIAL SKILLS COMPETENCIES Minimum 5to 6 years of experience in implementing AI and ML models Excellent problemsolving skills with the ability to work independently as well as collaboratively in a team Solid understanding of machine learning algorithms and principles and their applicability to different problems Proficiency in Python and familiarity with libraries like TensorFlow Keras PyTorch or similar ML libraries Experience with GenAI would be highly beneficial Strong communication and presentation skills Skills Mandatory Skills : Prompt Engineering & RAG Good to Have Skills : Fine Tuning Large Language Models Preferred candidate profile

machine learning algorithms and deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Proficiency in Python data processing libraries (Pandas, NumPy) Knowledge of cloud platforms like AWS, GCP, or Azure NLP,LLM,GenAI

We are looking for an AI Engineer (Senior Software Engineer). Interested candidates email me resumes on mayura.joshi@lionbridge.com OR WhatsApp on 9987538863 Responsibilities: Design, develop, and optimize AI solutions using LLMs (e.g., GPT-4, LLaMA, Falcon) and RAG frameworks. Implement and fine-tune models to improve response relevance and contextual accuracy. Develop pipelines for data retrieval, indexing, and augmentation to improve knowledge grounding. Work with vector databases (e.g., Pinecone, FAISS, Weaviate) to enhance retrieval capabilities. Integrate AI models with enterprise applications and APIs. Optimize model inference for performance and scalability. Collaborate with data scientists, ML engineers, and software developers to align AI models with business objectives. Ensure ethical AI implementation, addressing bias, explainability, and data security. Stay updated with the latest advancements in generative AI, deep learning, and RAG techniques. Requirements: 8+ years experience in software development according to development standards. Strong experience in training and deploying LLMs using frameworks like Hugging Face Transformers, OpenAI API, or LangChain. Proficiency in Retrieval-Augmented Generation (RAG) techniques and vector search methodologies. Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate. Solid understanding of NLP, deep learning, and transformer architectures. Proficiency in Python and ML libraries (TensorFlow, PyTorch, LangChain, etc.). Experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows. Familiarity with containerization (Docker, Kubernetes) for scalable AI deployments. Strong problem-solving and debugging skills. Excellent communication and teamwork abilities Bachelors or Masters degree in computer science, AI, Machine Learning, or a related field.

Design and build production-grade Python APIs, integrate LLMs using LangChain/LangGraph, and develop backend systems. Requires 5+ yrs in backend dev, strong Python, hands-on LLM integration, and experience with async workflows and deployment.

Position overview: We are seeking an experienced Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 3 to 6 years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Develop, Test, and Deploy machine learning models for various business and Telco use cases. Perform data preprocessing, feature engineering and ML/DL model evaluation. Optimize and fine-tune models for performance and scalability. Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT Build and refine RAG models to improve information retrieval and answer generation systems. Integrate RAG methods into existing applications to enhance data accessibility and user experience. Work closely with cross-functional teams including software engineers, product managers, and domain experts. Communicate technical concepts to non-technical stakeholders effectively. Document processes, methodologies, and model development for internal and external stakeholders. Skills: Bachelors or masters degree in Computer Science, Data Science, Statistics, Mathematics, or a related field from reputed institutions. Strong knowledge of probability and statistics. Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge – Python, SQL and commonly used frameworks & tools – PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding tests.

equired Skills & Qualifications Education & Experience: Bachelors or Master’s degree in Computer Science, Data Science, or a related field. 3–5 years of hands-on experience developing AI or data-driven applications in Python. Technical Expertise: LangChain: Proficiency in designing and implementing RAG pipelines. AWS Bedrock/ Azure OpenAI: Familiarity with integrating large language models. Pydantic: Solid understanding of data validation and configuration management. LangGraph: Experience with workflow orchestration and state management. FastAPI & React: Experience building RESTful APIs and integrating front-end frameworks. AWS: Practical knowledge of cloud deployment, CI/CD, and infrastructure management. Pinecone: Familiarity with hybrid retrieval techniques (sparse + dense), similarity search configurations, and metadata filtering. Soft Skills: Excellent problem-solving abilities and attention to detail. Strong communication skills, with the ability to explain complex AI concepts to non- technical stakeholders. A team player who thrives in a collaborative environment. Experience with Docker or Kubernetes for containerization and orchestration. Knowledge of MLOps tools and practices (e.g., MLflow, Airflow, etc.). Familiarity with other vector databases or vector search engines.

Job Description for GB5A(Dev) Primary Role Primarily responsible for working as Tech Lead i.e. leading the team and mentoring it technically. Provide hands-on technical leadership in the design, development, and deployment of generative AI models and systems. Serve as the technical point of contact for cross-functional teams, ensuring seamless collaboration between product, engineering, and data science teams. Responsibilities & KPIs Guiding the team technically and helping them solve the technical problems, throughout the project. Responsible for defining project goals, timelines, and deliverables in collaboration with stakeholders. Ensure scalability, robustness, and cost-efficiency of AI solutions. Conduct code reviews, provide constructive feedback, and ensure adherence to best practices in AI development. Build and maintain workflows to manage multiple POCs and project workloads efficiently. Collaborate with data scientists and domain experts to ensure model accuracy and relevance. Architect end-to-end Generative AI pipelines for model training, evaluation, and deployment using state-of-the-art tools and techniques Optimize AI models for speed, accuracy, and cost-efficiency. Ensure compliance with security and ethical standards. Address challenges like data drift and model degradation Proactively introduce innovative generative AI methodologies to address complex business challenges. Foster a culture of experimentation and continuous learning within the team. Ensure alignment between business goals and technical implementations. Desired Skills B.E./B.Tech degree in Computer Science, Information Science, or a related field from a leading institute preferred. Good leadership and people management skills. Excellent communication skills for translating technical concepts to non-technical stakeholders. Hands-on experience with Python Hands-on experience in machine learning, natural language processing, deep learning, and Generative AI technologies like LLM, RAG, Multi Modal architecture. Familiarity with frameworks like TensorFlow, PyTorch, Keras or Hugging Face. Familiarity with MLOps and CI/CD pipelines for AI workflows. Knowledge of cloud platforms (AWS, Azure, or GCP) for deploying AI solutions. Familiarity with current AI trends and open source technologies. Strong problem-solving and analytical skills. Ability to work on multiple projects simultaneously and manage priorities effectively. Exposure to financial services domains is a plus. Basic understanding of UI Frameworks (e.g. Angular) is a plus.

Are you ready to shape the future of AI? As a Mid-Level Generative AI Engineer at Techolution, you'll be at the forefront of innovation, fine-tuning cutting-edge LLMs like Falcon, LLaMA, and PaLM 2. Dive deep into the world of NLP, vector databases, and deep learning frameworks to create groundbreaking solutions. Your expertise in Python, PyTorch, and TensorFlow will drive the development of next-generation AI applications. Join our dynamic team and turn visionary concepts into reality, while collaborating with cross-functional experts to integrate ML solutions that redefine industries. Designation: Generative AI Engineer Location: Hyderabad, India Employment Type: Full Time Expertise: Mid-Level Key Responsibilities Develop and implement cutting-edge generative AI solutions, leveraging LLMs and RAG techniques to solve complex business challenges and drive innovation. Design and optimize AI agents that automate tasks, enhance decision-making processes, and improve overall operational efficiency across various departments. ¢ Spearhead the implementation of vector databases to efficiently store and retrieve high-dimensional data, enabling faster and more accurate AI model performance. ¢ Lead the fine-tuning of pre-trained models, adapting them to specific use cases and improving their performance on domain-specific tasks. ¢ Collaborate with cross-functional teams to integrate generative AI capabilities into existing products and services, enhancing user experiences and creating new value propositions. ¢ Conduct thorough research on emerging deep learning techniques and architectures, staying at the forefront of AI advancements and applying them to real-world problems. ¢ Develop and maintain scalable AI pipelines that streamline data processing, model training, and deployment processes, ensuring efficient and reliable AI operations. ¢ Demonstrate strong ownership by taking responsibility for end-to-end AI project lifecycles, from concept to production deployment and ongoing optimization. ¢ Cultivate a seeker mindset by continuously exploring new AI methodologies and tools, actively contributing to the team's knowledge base and fostering a culture of innovation. ¢ Showcase passion towards work by eagerly tackling complex AI challenges, pushing boundaries, and consistently delivering high-quality solutions that exceed expectations. Foundational Skills ¢ Large Language Models (LLMs): Proven expertise in working with state-of-the-art LLMs, including fine-tuning, prompt engineering, and integration into production systems. ¢ Retrieval-Augmented Generation (RAG): Demonstrated ability to implement RAG techniques to enhance AI model performance and accuracy in information retrieval tasks. ¢ Fine-tuning: Proficiency in adapting pre-trained models to specific domains and tasks, optimizing their performance for targeted applications. ¢ Vector Databases: Hands-on experience with vector databases for efficient storage and retrieval of high-dimensional data in AI applications. ¢ Deep Learning: Strong foundation in deep learning principles and architectures, with the ability to apply them to solve complex real-world problems. ¢ Generative AI: Comprehensive understanding of generative AI techniques and their practical applications in various industries. ¢ AI Agents: Experience in designing and implementing AI agents that can autonomously perform tasks and make decisions. ¢ Ownership: Demonstrated ability to take full responsibility for projects, driving them from conception to successful completion. ¢ Seeker Mindset: Proactive approach to learning and exploring new technologies, constantly seeking ways to improve and innovate. ¢ Passionate Towards Work: Genuine enthusiasm for AI and its potential to transform industries, reflected in a commitment to excellence and continuous improvement. ¢ Extremely Ambitious: Drive to push boundaries and set high goals, both personally and for the team, to achieve groundbreaking results in AI development. ¢ Ability to Comprehend: Exceptional skill in quickly grasping complex AI concepts and translating them into practical, impactful solutions. Advanced Skills ¢ Computer Vision: Familiarity with computer vision techniques and frameworks, enabling the integration of visual data processing capabilities into AI solutions. ¢ Cloud Deployment: Experience with deploying AI models and applications on cloud platforms, ensuring scalability and reliability in production environments. ¢ Leadership Experience: Prior experience in leading small teams or mentoring junior engineers, demonstrating potential for future growth into leadership roles within the AI department. How to Apply If you are passionate about leveraging AI technologies to create impactful solutions and meet the qualifications listed above, we invite you to apply for this exciting opportunity by sharing your video resume. We look forward to hearing your story and exploring how your skills align with the goals of our team. As an equal opportunity employer, Techolution celebrates diversity and is committed to creating an inclusive environment for all employees. About Techolution At Techolution, we specialize in building custom AI solutions that deliver innovation and drive measurable outcomes for enterprises worldwide. With our specialized expertise we help businesses take AI from their labs into the real world. What We Do As your one-stop shop engineering firm, Techolution guides you from ideation to ROI realization. We ensure real-world AI success by minimizing R&D risks for our clients with our innovative fixed-bid pricing model. Our Unique Value Proposition ¢ White Glove Service: From Ideation Innovation Integration, we lead the way to deliver meaningful outcomes, enabling your team to operate AI solutions independently. ¢ Human-AI Partnership: Our Govern Guide Control (GGC) framework ensures responsible AI governance, aligning solutions with your organizational requirements and brand identity. ¢ Customized AI Solutions: We tailor AI to your enterprise needs, delivering from concept to implementation with our turnkey approach at a guaranteed price. Our Impact Techolution has partnered with 300+ clients worldwide, including 50+ Fortune 500 companies. Our growing team works across diverse sectors such as healthcare, education, retail, media, tech, banking, fintech, government, telecom, and manufacturing. Celebrating 9+ years in business, we are committed to AI Done Right! Awards & Recognition ¢ 2024: Forbes publishes the best-selling book by our CEO, "Failing Fast?: The 10 Secrets to Succeed Faster." ¢ 2023: AI Solutions Provider of the Year - AI Summit ¢ 2022: Best in Business Award - Inc. Magazine ¢ 2021: Best Cloud Transformation Consulting - CIO Review ¢ 2019: Inc. 500 Fastest Growing Company Award Take a Look At Our Accelerators ¢ Enterprise LLM Studio ¢ AppMod.AI ¢ ComputerVision.AI ¢ Robotics and Edge Device Fabrication ¢ RLEF AI Platform Some Videos You Wanna Watch! ¢ About Techolution ¢ Transform Customer Service with Techolution ¢ GoogleNext 2023 ¢ Conversational AI for Enterprise ¢ Realytics AI Success Story Visit us at www.techolution.com to know more about our revolutionary core practices and how we enrich the human experience with technology.

Role & responsibilities Preferred candidate profile We're seeking a skilled Python developer with a focus on building advanced agentic applications. In this role, you'll architect and implement autonomous AI systems that can reason, plan, and execute complex tasks with minimal human intervention. Core Responsibilities Design and develop agentic AI applications using Python and modern frameworks Implement and optimize Retrieval-Augmented Generation (RAG) systems for knowledge-intensive applications Create scalable backend services using FastAPI and Django Collaborate with cross-functional teams to define agent architectures and workflows Develop testing frameworks to evaluate agent performance and reliability Document technical approaches, system architectures, and implementation details Technical Requirements Strong proficiency in Python programming and software engineering best practices Experience building web applications with FastAPI and/or Django frameworks Practical experience implementing RAG systems and understanding of vector databases Familiarity with prompt engineering techniques and LLM capabilities/limitations Knowledge of containerization, CI/CD pipelines, and deployment strategies Nice-to-Have Skills Experience with agentic frameworks like LangGraph or CrewAI Background in fine-tuning open-source models (e.g., Llama, Mistral, Falcon) Understanding of multi-agent systems and coordination protocols Experience with tools like LlamaIndex, LangChain, or similar LLM orchestration libraries Familiarity with reinforcement learning from human feedback (RLHF) Contributions to open-source AI projects Technical Environment You'll be working with cutting-edge technologies including: Python 3.x ecosystem FastAPI and Django for backend development Vector databases (e.g., Pinecone, Milvus, or Weaviate) LLM orchestration frameworks Modern cloud infrastructure (AWS/GCP/Azure) What We're Looking For Problem solvers who enjoy tackling complex technical challenges Self-motivated learners who stay current with rapidly evolving AI technologies Engineers who can balance theoretical understanding with practical implementation Strong communicators who can explain technical concepts to various stakeholders Join us to push the boundaries of what's possible with agentic AI systems and help shape the future of autonomous applications.

Role: AI/ML Engineer Has 4+ years of work experience , with at least 2+ years directly working on Generative AI and Agentic systems Knows how to use Large Language Models (LLMs) like GPT for real applications (not just research or theory) Has worked on multi-agent systems or autonomous AI agents using tools like CrewAI, AutoGen, or similar frameworks Can write smart prompts ( prompt engineering ), build apps with LLMs, and knows how to do RAG (Retrieval-Augmented Generation) Has done fine-tuning of models and built custom AI workflows Codes well in Python Has used ML frameworks like TensorFlow or PyTorch Familiar with tools like LangChain , and cloud/data platforms like AWS or Databricks Location: Bangalore/ Mumbai Shift Timing: 12:00 PM 9:00 PM Notice Period: 30 days or less Call Anumeha @ +91 6376649769/ Alfiya @ +91 8787064649

What Youll Own Full Stack Systems: Architect and build end-to-end applications using Flask, FastAPI, Node.js, React (or Next.js), and Tailwind. AI Integrations: Build and optimize pipelines involving LLMs (OpenAI, Groq, LLaMA), Whisper, TTS, embeddings, RAG, LangChain, LangGraph, and vector DBs like Pinecone/Milvus. Cloud Infrastructure: Deploy, monitor, and scale systems on AWS/GCP using EC2, S3, IAM, Lambda, Kafka, and ClickHouse. Real-time Systems: Design asynchronous workflows (Kafka, Celery, WebSockets) for voice-based agents, event tracking, or search indexing. System Orchestration: Set up scalable infra with autoscaling groups, Docker, and Kubernetes (PoC ready, if not full prod). Growth-Ready Features: Implement in-app nudges, tracking with Amplitude, AB testing, and funnel optimization. Tech Stack Youll Work With: Backend & Infrastructure Languages/Frameworks: Python (Flask, FastAPI), Node.js Databases: PostgreSQL, Redis, ClickHouse Infra: Kafka, Docker, Kubernetes, GitHub Actions, Cloudflare Cloud: AWS (EC2, S3, RDS), GCP Frontend React / Next.js, TailwindCSS, Zustand, Shadcn/UI WebGL, Three.js for 3D rendering AI/ML & Computer Vision LangChain, LangGraph, HuggingFace, OpenAI, Groq Whisper (ASR), Eleven Labs (TTS) Diffusion Models, StyleGAN, Stable Diffusion GANs, MediaPipe, ARKit/ARCore Computer Vision: Face tracking, real-time try-on, pose estimation Virtual Try-On: Face/body detection, cloth/hairstyle try-ons APIs Stripe, VAPI, Algolia, OpenAI, Amplitude Vector DB & Search Pinecone, Milvus (Zilliz), custom vector search pipelines Other Vibe Coding culture, prompt engineering, system-level optimization Must-Haves: 1+ years of experience building production-grade full-stack systems Fluency in Python and JS/TS (Node.js, React) shipping independently without handholding Deep understanding of LLM pipelines, embeddings, vector search, and retrieval-augmented generation (RAG) Experience with AR frameworks (ARKit, ARCore), 3D rendering (Three.js), and real-time computer vision (MediaPipe) Strong grasp of modern AI model architectures: Diffusion Models, GANs, AI Agent Hands-on with system debugging, performance profiling, infra cost optimization Comfort with ambiguity fast iteration, shipping prototypes, breaking things to learn faster Bonus if youve built agentic apps, AI workflows, or virtual try-ons

Develop and deploy AI-based applications leveraging LLMs and Generative AI models like GPT, Gemini, or similar frameworks Build scalable backend systems using Python, ensuring seamless integration with UI/UX components Design and optimize generative AI models to address diverse business challenges Fine-tune pre-trained LLMs to align with specific use cases Work closely with cross-functional teams, including data scientists, UI/UX developers, and product managers, to deliver robust solutions Collaborate with clients to gather requirements and develop customized AI capabilities Deploy solutions on cloud platforms (Azure, AWS, or GCP) and ensure system scalability and performance

Sr. GenAI Engineer Manager Role Overview: As a Sr. GenAI Engineer , you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users, while also driving tangible value for business investments. You will leverage your extensive GenAI & engineering craftsmanship and advanced proficiency across multiple programming languages and modern frameworks, consistently demonstrating your exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player and mentor, collaborating with cross-functional teams to design, develop, and deploy advanced software solutions. Key Responsibilities: Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations. Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, contributing to low-level architecture and component design, development, unit testing, integrations, and support. Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate. Create technical specifications, and write high-quality, supportable, scalable code and review code of other engineers, mentoring them, to ensure all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams. Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate strong understanding of the full lifecycle product development, focusing on continuous improvement and learning. Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. Key Qualifications: A bachelors degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. Excellent software engineering foundation with deep understanding of OOP/OOD, sequence/activity/state/ER/DFD diagrams, data-structure, algorithms, code instrumentations, etc. 10-13 years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc. Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc. Strong understanding and experience in managing big data of various forms to generate insights and create intelligence. Proven experience with Angular, React, NodeJS, Python, Streamlit, C#, .NET Core, Golang, SQL/NoSQL. Proven experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP. Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc. to deliver high quality products rapidly. Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

Role & responsibilities Generative AI, NLP & MLE: Design, develop, deploy, and scale advanced applications using Generative AI models (e.g., GPT, LLaMA, Mistral), NLP techniques, and MLE/MLOps best practices to solve business challenges and unlock new opportunities. Model Customization & Fine-Tuning: Apply techniques such as LoRA, PEFT, and fine-tuning of LLMs to build domain-specific models aligned with business use cases, with a focus on making them deployable in real-world environments. ML Engineering & Deployment: Implement end-to-end ML pipelinesincluding data preprocessing, model training, versioning, testing, and deploymentusing tools like MLflow, Docker, Kubernetes, and CI/CD practices. Innovative Problem Solving: Leverage cutting-edge AI and ML methodologies to solve practical business problems and deliver measurable results. Scalable AI Solutions: Ensure robust deployment, monitoring, and retraining of models in production environments, working closely with data engineering and platform teams. Data-Driven Insights: Conduct deep analysis of structured and unstructured data to uncover trends, guide decisions, and optimize AI models. Cross-Functional Collaboration: Partner with Consulting, Engineering, and Platform teams to integrate AI/ML solutions into broader architectures and business strategies. Client Engagement: Work directly with clients to understand requirements, present tailored AI solutions, andprovide advice on the adoption and operationalization of Generative AI and ML. Preferred candidate profile Overall 5-9 years of experience with real-time experience in GenAI and MLE/MLOps. Expertise in Generative AI: Hands-on experience in designing and deploying LLM-based solutions with frameworks such as HuggingFace, LangChain, Transformers, etc. MLE & Production Readiness: Proven experience in building ML models that are scalable, reliable, and production-ready, including exposure to MLE/MLOps workflows and tools. Deployment Tools & Best Practices : Familiarity with containerization (Docker), orchestration (Kubernetes), model tracking (MLflow), and cloud platforms (AWS/GCP/Azure) for deploying AI solutions at scale. Proficiency in development using Python frameworks (such as Django/Flask) or other similar technologies. In-depth understanding of APIs, microservices architecture, and cloud-based deployment strategies. Innovation & Curiosity: A passion for staying updated with the latest in Gen AI, LLMs, and ML engineering practices. Communication : Ability to translate complex technical concepts into business-friendly insights and recommendations