492 Genai Jobs - Page 13

Roles and Responsibilities: The successful candidate will be responsible for the continuity of architecting our product. This includes- Collaboratively build, implement, and manage technology architecture roadmap. Implement, manage, and validate strong coding standard and quality across various technologies. Implement, manage, and drive core technology upgrades within the product roadmap. Lead by example and able to show case strong coding skills. Identify and develop next line of technical architects within the team. Prime both proactive and reactive stakeholders engagements. Build and maintain the Product API layer through API Management platforms like Postman, Swagger, Apiary etc. Technology Stack- • The following technology stacks are required, but not limited to: • Angular/React (experience with micro-frontend architecture will be an added advantage) • NodeJS, Python, JAVA • MongoDB or any NoSQL, Oracle, SQL Server, MySQL/PostgreSQL (experience with Data Pipeline creation and management will be an added avantage) • Redis or any other Caching technology • Jenkins and Serverless deployment • Docker, Kubernetes, Kong • Puppet, Chef, Ansible • RabbitMQ, Apache Kafka, Apache ActiveMQ, Amazon SQS or AmazonMQ

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

Python, Deep Learning, Object Detection, Classification, Segmentation., GPU acceleration (CUDA, cuDNN). Model Optimization (pruning, quantization), deploying models to edge devices. Required Candidate profile willingness to explore and contribute to Generative AI and cloud-based AI solutions, C/C++., AWS Cloud AI/ML tools, exposure to GenAI frameworks like OpenAI, Stable Diffusion

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Google Cloud Machine Learning Services Summary: As an AI/ML Engineer, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying GenAI models, developing cloud or on-prem application pipelines, and ensuring production-ready quality. You will also work with deep learning, neural networks, chatbots, and image processing. Key Responsibilities : A: Demonstrate various Google specific Designs using effective POCs, as per client requirements. B: Identifying applicability of Google Cloud AI services to use cases with ability to project both the business and tech benefits. C: Design, build and productionizes ML models to solve business challenges using Google Cloud technologies D: Lead and guide team of data scientists E: Coordinating and collaborating with cross-functional teams Technical Experience : A: Min 3 + years of experience on GCP AWS ML B: Exposure to Google Gen AI Services C: Exposure to GCP and its Compute, Storage, Data, Network, Security services D: Expert programming skills in any one of Java, Python, Spark E: Knowledge of GKE, Kubeflow on GCP would be good to have G: Experience in Vertex AI for building and managing the ML models H: Experience in implementing MLOps Location: Pan India

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 , 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 , 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 and on , , , and Inviting applications for the role of Principal Consultant -Lead MLOps Engineer! In this role, you will define, implement and oversee the MLOps strategy for scalable, compliant, and cost-efficient deployment of AI/ GenAI models across the enterprise. This role combines deep DevOps knowledge, infrastructure architecture, and AI platform design to guide how teams build and ship ML models securely and reliably. You will establish governance, reuse, and automation frameworks for AI infrastructure, including Terraform-first cloud automation, multi-environment CI/CD, and observability pipelines. Responsibilities Architect secure, reusable, modular IaC frameworks across cloud and regions for MLOps Lead the development of CI/CD pipelines and standardize deployment frameworks. Design observability and monitoring systems for ML/ GenAI workloads. Collaborate with platform, data science, compliance and Enterprise Architecture teams to ensure scalable ML operations. Define enterprise-wide MLOps architecture and standards (build ? deploy ? monitor) Lead design of GenAI / LLMOps platform (Bedrock/OpenAI/Hugging Face + RAG stack) Integrate governance controls (approvals, drift detection, rollback strategies) Define model metadata standards, monitoring SLAs, and re-training workflows Influence tooling, hiring, and roadmap decisions for AI/ML delivery Be engaging in the design, development and maintenance of data pipelines for various AI use cases Required to actively contribution to key deliverables as part of an agile development team Qualifications we seek in you! Minimum Qualifications Good years of experience in DevOps or MLOps roles. Degree/qualification in Computer Science or a related field, or equivalent work experience Strong Python programming skills. Hands on experience in containerised deployment. Proficient with AWS (SageMaker, Lambda, ECR), Terraform, and Python. Demonstrated experience deploying multiple GenAI systems into production. Hands-on experience deploying 3-4 ML/ GenAI models in AWS. Deep understanding of ML model lifecycle: train ? test ? deploy ? monitor ? retrain. Experience in developing, testing, and deploying data pipelines using public cloud. Clear and effective communication skills to interact with team members, stakeholders and end users Knowledge of governance and compliance policies, standards, and procedures Exposure to RAG/LLM workloads and model deployment infrastructure. Experience in developing, testing, and deploying data pipelines Preferred Qualifications/ Skills Experience designing model governance frameworks and CI/CD pipelines. Knowledge of governance and compliance policies, standards, and procedures Advanced understanding of platform security, cost optimization, and ML observability. 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.

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Lead Consultant, Data Analyst In this role, you will be working with the client team to solve their data analytics and automation needs. In Addition, client is trying to leverage data science techniques using a newly acquired platform &lsquoDataRobot to the build predictive models based upon tons of available enterprise data. DataRobot provides a simple, drag-and-drop web-based interface for building and deploying complex predictive models. But interpretation of these models and insights requires skills of a data scientist / engineer to harness this tool&rsquos capabilities fully and efficiently to the fullest. Responsibilities . Solve business problems using advanced data analytics tools like Python, R and GenAI/AI/ML solutions. . Collaborate with other client group members and stakeholders to provide data analytic support. . Executing data-driven processes by building models and frameworks that connect business unit drivers and forecast correct actions as per the business needs. . Evaluate automation opportunities suggested by the Service lines. . Maintain a prioritized backlog for development and implementation of automation solutions. . Fix bugs and enhance existing automation solutions. . End-to-end project management including day-to-day delivery, reporting, escalations etc. . Stakeholder management - Collaborate with client, tech teams and Genpact stakeholders to achieve project objectives. . Knowledge sharing and mentoring team members to enable them to handle data projects more efficiently and effectively. . Be able to work in high pressure environment. Qualifications Minimum qualifications . Any Graduate . MBA / M. Tech(preferred) . Agile Certified - good to have. . Should have prior experience in Data analysis and automation. Preferred qualifications . Strong Excel & VBA skills are a must. . Hands-on experience of DataRobot . Hands-on experience with advanced Python/R/SQL/ML . Data and Trend Analysis - Experience with predictive modelling techniques such as clustering, segmentation, linear & regression, random forest etc. . Working knowledge of GenAI is an added advantage. . Ability to design and build dashboards and other visualization in BI tools such as Tableau, Qlikview or Power BI . Good communication skills & highly proactive approach. . Ability to manage & prioritize deliverables. . Ability to learn and apply new processes and tools. . Process orientated awareness of Lean Six Sigma. 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. For more information, visit www.genpact.com . Follow us on Twitter, Facebook, LinkedIn, and YouTube. 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: Deputy Manager Strategy About the Role We are looking for a high-potential, entrepreneurial problem-solver to join our Strategy Team at Indofast a landmark Joint Venture between IndianOil and SUN Mobility, aimed at building India’s largest EV battery swapping network. You will work directly with CXOs and functional leaders to solve high-impact problems across commercial strategy, pricing design, financial analysis, AI/automation, and go-to-market (GTM) execution. If you’re a diligent, consistent worker with consulting prowess, love solving hard problems, and aspire to build the EV ecosystem of tomorrow, this role is your launchpad. Location: Bengaluru Experience: 1 – 2 years (minimum) Education: Bachelor’s degree from a Tier-1 engineering institutes; candidates with CFA/ CA plus tech/ quantitative backgrounds will also be considered favourably Key Responsibilities Financial Strategy & Pricing Build and evolve pricing structures for B2B and B2C business lines (across 2W, 3W, loaders) Analyse cost stacks, identify revenue leakages, and drive margin optimization Develop financial models to assess ROI on new initiatives and commercial pilots Strategic Initiatives Own and drive company-wide projects – from GTM strategy, next-year business planning, to investor decks and market intel updates Structure ambiguous problems and create frameworks for decision-making at leadership level Collaborate with cross-functional teams (Sales, Ops, Network, BD) to drive execution Data, AI & Automation Experiment with tools (e.g., GPT agents, Excel macros, PowerBI) to simplify execution Explore agent-based workflows to improve internal productivity and external CX Lead automation/AI-first workflows for operational & pricing dashboards What We’re Looking For Must-Haves 1+ years of experience in a startup / founder’s office, corp strategy, consulting and/or business finance Strong command of Excel and financial modelling; fluent in PowerPoint for CXO-level storytelling Exceptional problem-solving skills with structured thinking and data-first mindset Demonstrated ability to work hard, own outcomes, and work through ambiguity Good-to-Haves Experience in EV / clean tech / mobility / infra sectors Exposure to GenAI tools, automation workflows or scripting Passion for sustainability and India's energy transition Who You Are Sharp: You know how to deconstruct complex problems and solve them independently Coachable: You’re coachable and enjoy learning faster than your peers Hungry: You want to grow fast and are willing to roll up your sleeves to make it happen Mission-Driven: You care about green mobility, decarbonization and building India's future Why Indofast? At Indofast, we aim to make electric vehicles affordable and accessible to all. We believe electric vehicles are the future of mobility, and we strive to accelerate their adoption with our innovative battery swapping solutions. These solutions are interoperable across various vehicle platforms and form factors, making them future-proof, sustainable, and highly scalable. Joining us means being part of a front-row seat in India's EV journey. You'll get to: Work directly with ex-consultants, folk from top tier colleges, who are passionate, hardworking Solve problems that impact millions Build products and strategies at the bleeding edge of energy-tech and mobility

Job description: Data Scientist Specialist (NLP, LLM, and GenAI) Roles and responsibilities: • Collaborate with Product, Data, and Technology teams to design and create a suite of new microservices powered by AI • Work alongside a team of data scientists in applying state-of-the-art LLMs from OpenAI, Anthropic, Meta, and Mistral • Create NLP pipelines for Named Entity Recognition and Entity Resolution • Assess the quality and robustness of your solutions and iterate to optimize performance • Apply best practices of MLOps / LLMOps in deploying new products and services to production We expect you to have: • 7+ years processing structured and unstructured data using NLP • 1+ years applying LLMs and RAG to solve real-world, industry problems • Solid understanding of NLP and related concepts such as vectorization, entity resolution, string similarity, and semantic search • Python experience is required, AWS/ FastAPI / Gradio / Docker and LLM fine-tuning is a plus • Cloud and systems experience in AWS S3/EC2, Databricks, and linux • Solid understanding of Git or other version control software • Passionate about Generative AI, consistently tracking the latest industry developments • Strong organizational and communication skills, both verbal and written • Ambitious and enthusiastic about working in a fast-paced, startup style environment • Bachelor's degree in computer science, Computer Engineering, or related discipline. Masters preferred. It would be phenomenal if you: • Have previous experience crafting financial data products. • Have strong aptitude and/or interest in financial markets

Description - External Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities: Lead and manage a team of data scientists, fostering a collaborative and innovative environment Oversee the design and development of predictive models and machine learning algorithms Collaborate with business stakeholders to understand and define their data needs Translate business problems into data-driven solutions, presenting complex results in a clear and actionable manner Monitor model performance and continuously improve the accuracy of predictions and insights Maintain up-to-date knowledge of the latest data science trends and technologies, implementing new methodologies as appropriate Promote data literacy throughout the organization, educating staff on how to use data to drive decision-making Ensure data integrity and compliance with privacy regulations Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Role & responsibilities Required Qualifications: Bachelor of Engineering or equivalent 10+ years of total experience Coding : Python, pandas, numpy Math behind ML and DL algorithms Basics of Statistics ML and DL concepts Preferred Qualification: Exposure GenAI and LLMs Preferred candidate profile Perks and benefits

JD: Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning. Role & responsibilities Preferred candidate profile

Job Title: Senior Solution Architect Location : Bengaluru (WFO) Architectural Leadership: Serve as the Azure Solution Architect with specific sector knowledge, setting the direction for cloud architecture and ensuring alignment with the organization's technical strategy and O&G industry standards . Uphold industry best practices and standards specific to the O&G sector . Technology Roadmap: Construct and continuously update an Azure-focused technology roadmap, aligning with the organization's long-term goals. Explore and identify cutting-edge Azure services and features that can propel technological advancement. Strategically plan and implement upgrades to bolster the organization's competitive position and enhance the scalability of Azure-based solutions. Solution Design: Take the lead in design and architecture complex Azure solutions , with a strong focus on ensuring scalability, robust security, and cost-effectiveness and alignment with nuanced demands of the O&G industry. Stakeholder Engagement: Work in tandem with various service lines, such as engineering divisions and business stakeholders, to align Azure architectural strategies with the core business objectives and ensure the designs are in sync with the business's forward direction. Possess the ability to effectively communicate Azure technical strategies to non-technical stakeholders, thereby facilitating their participation in informed decision-making. Mentorship and Guidance: Offer Azure technical leadership and mentorship to solution squads. an environment of innovation, continuous improvement, and technical prowess across the organization. Cultivate Compliance and Best Practices: Guarantee Azure solutions meet regulatory demands and O&G-specific standards, including those related to safety, environment, and operations. Risk Assessment: Proactively identify and assess technical risks linked with Azure infrastructure and applications. Collaborate with multifaceted teams to formulate and implement measures to alleviate the detected risks. As a Solution Architect, it is crucial to pinpoint potential risks during the solution development phase and devise comprehensive risk mitigation plans for all solutions crafted. Industry Expertise: Stay informed about emerging technologies, trends, and standards in the oil and gas industry. Evaluate the potential impact of new technologies and provide recommendations for adoption both in upcoming solution designs as well as enhancement of solution architectures. Vendor Management: Engage with external vendors and technology associates to scrutinize third-party offerings compatible with Azure. Integrate these third-party solutions effortlessly, ensuring they complement and reinforce the broader Azure architectural strategy and the business objectives. Masters (or) Bachelor’s degree in Computer Science, Engineering, or Information Technology or a related field (or equivalent experience). Over all 8+ years of experience required for Solution Architect 8+ years of prior experience as a solution architect, preferably in the oil and gas industry or 8+ years of prior experience as a software engineer or similar role. Extensive experience in the oil and gas sector, including knowledge of industry-specific challenges and opportunities. Technical Expertise: Strong experience should have an in-depth understanding of Azure services and architecture, including IaaS, PaaS, and SaaS solutions. They should be adept at designing and implementing complex cloud infrastructure, ensuring scalability, reliability, and security. Also, strong experience in multi-cloud environments like AWS, GCP and their application migrations and management in O&G specifically. Advanced Problem-Solving: They must possess strong analytical skills to troubleshoot and resolve high-level technical issues. This includes the ability to perform root cause analysis and implement long-term solutions to prevent recurrence. Strategic Planning: The architect should be capable of developing strategic plans for cloud adoption and migration, aligning with the organization's goals. They should be able to evaluate and recommend new technologies and approaches to drive continuous improvement. Communication Skills: Excellent communication skills are essential for translating technical concepts to non-technical stakeholders, facilitating clear and effective discussions between cross-functional teams, and presenting proposals and progress reports to senior management. Client Engagement: Capable to work closely with clients (internal clients) to understand their business requirements and constraints, ensuring that the cloud solutions designed meet their needs and expectations. Innovation: With extensive experience, they should be at the forefront of innovation, exploring new cloud technologies and methodologies, and integrating them into the organization's practices to gain competitive advantage. Leadership and Mentorship: As a seasoned leader, the Senior Solution Architect should set the technical direction and make pivotal decisions that define the organization's cloud strategy, while also serving as a mentor to uplift junior architects and engineers. They must lead by example, inspiring teams through complex initiatives and fostering professional growth by imparting knowledge, best practices, and constructive feedback to nurture the next generation of technical experts. Must have Master’s or Bachelor’s degree in computer science engineering or information technology or Relevant field. Relevant certifications such as Microsoft Certified: Azure Solutions Architect Expert or similar. Microsoft AZ900 Certification & AZ 305 Certification TOGAF or ArchiMate or Zachman or equivalent architecture frameworks experience Experience in automation using Python, Gen AI, AI Ops, etc. Experience with data integration, data warehousing, and big data technologies. Experience with containerization and orchestration tools (e.g., any 2 of following: Docker, OpenShift, Kubernetes, ECS, GKE, AKS, EKS, Rancher, Apache Mesos, Nomad, Docker Swarm, Kubernetes). Understanding of the O&G sector's operational workflows, including the intricacies of exploration, extraction, refining, and distribution activities, to tailor cloud-based solutions that complement the industry's unique needs. Competence in tackling technical hurdles specific to the O&G domain, such as efficient asset management in isolated areas, processing extensive seismic datasets, and ensuring compliance with strict regulatory frameworks. Proficiency in leveraging Azure cloud technologies to enhance the O&G Industry's operational effectiveness, utilizing tools like IoT, advanced data analytics, and machine learning for better results Experience with CI/CD pipelines and automated testing frameworks (e.g. CircleCI, Jenkins, TeamCity, Travis CI, Bamboo, Bitbucket, etc.) Strong interpersonal skills with the ability to engage effectively with both technical and non-technical stakeholders. Role & responsibilities Preferred candidate profile

Key Responsibilities: LLM Integration & Development: Build and fine-tune LLMs for task-specific applications using techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model adaptation. AI Agent Engineering: Design, develop, and orchestrate AI agents capable of reasoning, planning, tool use (e.g., APIs, plugins), and autonomous execution for user-defined goals. GenAI Use Case Implementation: Deliver GenAI-powered solutions such as chatbots, summarizers, document Q&A systems, assistants, and co-pilot tools using frameworks like LangChain or LlamaIndex. System Integration: Connect LLM-based agents to external tools, APIs, databases, and knowledge sources for real-time, contextualized task execution. Performance Tuning: Optimize model performance, cost-efficiency, safety, and latency using caching, batching, evaluation tools, and monitoring systems. Collaboration & Documentation: Work closely with AI researchers, product teams, and engineers to iterate quickly. Maintain well-structured, reusable, and documented codebases. Required Qualifications: 35 years of experience in AI/ML, with at least 12 years hands-on with GenAI or LLMs. Strong Python development skills and experience with ML frameworks (e.g., Hugging Face, LangChain, OpenAI API, Transformers). Familiarity with LLM orchestration, vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding models. Understanding of prompt engineering, agent architectures, and conversational AI flows. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. Preferred Qualifications: Experience deploying AI systems in cloud environments (AWS/GCP/Azure) or with containerized setups (Docker/Kubernetes). Familiarity with open-source LLMs (LLaMA, Mistral, Mixtral, etc.) and open-weight tuning methods (LoRA, QLoRA). Exposure to RAG pipelines, autonomous agents (e.g., Auto-GPT, BabyAGI), and multi-agent systems. Knowledge of model safety, evaluation, and compliance standards in GenAI.

Key Responsibilities: LLM Integration & Development: Build and fine-tune LLMs for task-specific applications using techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model adaptation. AI Agent Engineering: Design, develop, and orchestrate AI agents capable of reasoning, planning, tool use (e.g., APIs, plugins), and autonomous execution for user-defined goals. GenAI Use Case Implementation: Deliver GenAI-powered solutions such as chatbots, summarizers, document Q&A systems, assistants, and co-pilot tools using frameworks like LangChain or LlamaIndex. System Integration: Connect LLM-based agents to external tools, APIs, databases, and knowledge sources for real-time, contextualized task execution. Performance Tuning: Optimize model performance, cost-efficiency, safety, and latency using caching, batching, evaluation tools, and monitoring systems. Collaboration & Documentation: Work closely with AI researchers, product teams, and engineers to iterate quickly. Maintain well-structured, reusable, and documented codebases. Required Qualifications: 35 years of experience in AI/ML, with at least 12 years hands-on with GenAI or LLMs. Strong Python development skills and experience with ML frameworks (e.g., Hugging Face, LangChain, OpenAI API, Transformers). Familiarity with LLM orchestration, vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding models. Understanding of prompt engineering, agent architectures, and conversational AI flows. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. Preferred Qualifications: Experience deploying AI systems in cloud environments (AWS/GCP/Azure) or with containerized setups (Docker/Kubernetes). Familiarity with open-source LLMs (LLaMA, Mistral, Mixtral, etc.) and open-weight tuning methods (LoRA, QLoRA). Exposure to RAG pipelines, autonomous agents (e.g., Auto-GPT, BabyAGI), and multi-agent systems. Knowledge of model safety, evaluation, and compliance standards in GenAI.

Key Responsibilities: LLM Integration & Development: Build and fine-tune LLMs for task-specific applications using techniques like prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model adaptation. AI Agent Engineering: Design, develop, and orchestrate AI agents capable of reasoning, planning, tool use (e.g., APIs, plugins), and autonomous execution for user-defined goals. GenAI Use Case Implementation: Deliver GenAI-powered solutions such as chatbots, summarizers, document Q&A systems, assistants, and co-pilot tools using frameworks like LangChain or LlamaIndex. System Integration: Connect LLM-based agents to external tools, APIs, databases, and knowledge sources for real-time, contextualized task execution. Performance Tuning: Optimize model performance, cost-efficiency, safety, and latency using caching, batching, evaluation tools, and monitoring systems. Collaboration & Documentation: Work closely with AI researchers, product teams, and engineers to iterate quickly. Maintain well-structured, reusable, and documented codebases. Required Qualifications: 35 years of experience in AI/ML, with at least 12 years hands-on with GenAI or LLMs. Strong Python development skills and experience with ML frameworks (e.g., Hugging Face, LangChain, OpenAI API, Transformers). Familiarity with LLM orchestration, vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding models. Understanding of prompt engineering, agent architectures, and conversational AI flows. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field. Preferred Qualifications: Experience deploying AI systems in cloud environments (AWS/GCP/Azure) or with containerized setups (Docker/Kubernetes). Familiarity with open-source LLMs (LLaMA, Mistral, Mixtral, etc.) and open-weight tuning methods (LoRA, QLoRA). Exposure to RAG pipelines, autonomous agents (e.g., Auto-GPT, BabyAGI), and multi-agent systems. Knowledge of model safety, evaluation, and compliance standards in GenAI.

15 years of experience in software engineering, with at least 5 years of experience in a leadership role. Strong technology expertise in Java, Microservices architecture, AWS cloud platform, AI, and the Angular framework. Solid background in building scalable and distributed systems, with expertise in technologies such as Spring boot (Spring (Core, AOP, Transactions, Data, Security), Cassandra, Kubernetes (K8s), Kafka, Docker and others. Experience with security best practices and protocols (e.g., SSL/TLS, OAuth) Hand on experience towards Architecture and Design patterns. Practice industry's leading best guidelines/processes in building enterprise products/components Proven track record of successfully leading and managing high-performing engineering teams. Excellent communication, interpersonal, and leadership skills. Ability to mentor and coach others, helping them develop their technical and leadership skills. Strong problem-solving and analytical skills. Experience with Agile development methodologies. Ability to prioritize effectively and manage multiple tasks simultaneously. Experience in building and scaling software applications. Experience in recruiting and hiring top-tier engineering talent. Ability to work effectively in a cross-functional team environment. Skills: ssl/tls,software,agile development methodologies,spring boot,kubernetes,java,security best practices,microservices architecture,agile methodologies,leadership,kafka,architecture and design patterns,ai,aws cloud platform,docker,kubernetes (k8s),aws,oauth,angular,cassandra

Role & responsibilities Key Responsibilities Design, develop, and optimize machine learning models for various business applications. Build and maintain scalable AI feature pipelines for efficient data processing and model training. Develop robust data ingestion, transformation, and storage solutions for big data. Implement and optimize ML workflows, ensuring scalability and efficiency. Monitor and maintain deployed models, ensuring performance, reliability, and retraining when necessary Qualifications and Experience Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3.5 to 5 years of experience in machine learning, deep learning, or data science roles. Proficiency in Python and ML frameworks/tools such as PyTorch, Langchain Experience with data processing frameworks like Spark, Dask, Airflow and Dagster Hands-on experience with cloud platforms (AWS, GCP, Azure) and ML services. Experience with MLOps tools like ML flow, Kubeflow Familiarity with containerisation and orchestration tools like Docker and Kubernetes. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and collaboration skills. Preferred candidate profile

15 years of experience in software engineering, with at least 5 years of experience in a leadership role. Strong technology expertise in Java, Microservices architecture, AWS cloud platform, AI, and the Angular framework. Solid background in building scalable and distributed systems, with expertise in technologies such as Spring boot (Spring (Core, AOP, Transactions, Data, Security), Cassandra, Kubernetes (K8s), Kafka, Docker and others. Experience with security best practices and protocols (e.g., SSL/TLS, OAuth) Hand on experience towards Architecture and Design patterns. Practice industry's leading best guidelines/processes in building enterprise products/components Proven track record of successfully leading and managing high-performing engineering teams. Excellent communication, interpersonal, and leadership skills. Ability to mentor and coach others, helping them develop their technical and leadership skills. Strong problem-solving and analytical skills. Experience with Agile development methodologies. Ability to prioritize effectively and manage multiple tasks simultaneously. Experience in building and scaling software applications. Experience in recruiting and hiring top-tier engineering talent. Ability to work effectively in a cross-functional team environment. Skills: ssl/tls,software,agile development methodologies,spring boot,kubernetes,java,security best practices,microservices architecture,agile methodologies,leadership,kafka,architecture and design patterns,ai,aws cloud platform,docker,kubernetes (k8s),aws,oauth,angular,cassandra

Job Summary This position provides leadership in full systems life cycle management (e.g., analyses, technical requirements, design, coding, testing, implementation of systems and applications software, etc.) to ensure delivery is on time and within budget. He/She directs component and data architecture design, technology planning, and testing for Applications Development (AD) initiatives to meet business requirements and ensure compliance. This position develops and leads AD project activities and integrations. He/She guides teams to ensure effective communication and achievement of objectives. This position researches and supports the integration of emerging technologies. He/She provides knowledge and support for applications development, integration, and maintenance. This position leads junior team members with project related activities and tasks. He/She guides and influences department and project teams. This position facilitates collaboration with stakeholders. Responsibilities: Leads systems analysis and design. Leads design and development of applications. Develops and ensures creation of application documents. Defines and produces integration builds. Monitors emerging technology trends. Leads maintenance and support. Primary Skiils: Senior App Developer on GenAI Projects - As a Senior GenAI developer you will participate in all aspects of the software development lifecycle which includes estimating, technical design, Build and test, implementation, documentation, code review, testing, deployment, and support of application developed. Performs System Design and build GenAI projects via Agile methodologies. As a member working in a team environment, you will work with solution architects and developers on deciphering solution designs into functional requirements, and subsequently into technical design. 7 plus Years of Experience and hands on experience in GenAI projects with Cloud computing platforms (preferably Google Cloud) working experience. Proficiency in languages such as, Python and/or scripting languages Hands on experience and exposure to different models in GenAI Knowledge of software version control systems such as Git Experience with containerization technologies such as Docker or Kubernetes Secondary Skills: Passionate coder with 7+ years of delivering solutions, preferably with a focus on end-to-end project life cycle, must demonstrate GenAI delivery experience. Knowledge and experience in developing software using agile methodologies as well as Scrum lead experience. 'Skilled problem solvers & critical thinker with the desire and proven ability to create innovative solutions. Proficient communicators who can explain and present concepts to technical and non-technical audiences alike, including high level decision makers. Excellent analytical and technical skills Excellent written and verbal communication skills) Excellent planning and organizational skills Excellent interpersonal skills in areas such as teamwork, facilitation Qualifications: Bachelors Degree or International equivalent Bachelor's Degree or International equivalent in Computer Science, Information Systems, Mathematics, Statistics, or related field - Preferred

15 years of experience in software engineering, with at least 5 years of experience in a leadership role. Strong technology expertise in Java, Microservices architecture, AWS cloud platform, AI, and the Angular framework. Solid background in building scalable and distributed systems, with expertise in technologies such as Spring boot (Spring (Core, AOP, Transactions, Data, Security), Cassandra, Kubernetes (K8s), Kafka, Docker and others. Experience with security best practices and protocols (e.g., SSL/TLS, OAuth) Hand on experience towards Architecture and Design patterns. Practice industry's leading best guidelines/processes in building enterprise products/components Proven track record of successfully leading and managing high-performing engineering teams. Excellent communication, interpersonal, and leadership skills. Ability to mentor and coach others, helping them develop their technical and leadership skills. Strong problem-solving and analytical skills. Experience with Agile development methodologies. Ability to prioritize effectively and manage multiple tasks simultaneously. Experience in building and scaling software applications. Experience in recruiting and hiring top-tier engineering talent. Ability to work effectively in a cross-functional team environment. Skills : angular,ssl/tls,agile development methodologies,spring boot,kafka,aws cloud platform , docker , leadership , java , kubernetes , ai , microservices architecture , software , cassandra , security best practices,agile methodologies,oauth,kubernetes (k8s),aws

Position - Lead Machine Learning Engineer- MLOps, VertexAI, LLMs, GenAI, ML Model Management Role Overview UPS Data Science and Machine Learning team is seeking a highly skilled and experienced Lead Machine Learning Engineer to manage our AI, ML, GenAI application focused on Cross Border logistics. This position leverages continuous integration and deployment of the best practices, including test automation and monitoring, to ensure successful deployment of optimal ML models and analytical systems. You will be responsible for the end-to-end lifecycle of AI models, from experimentation and fine-tuning to deployment and management in production. A strong background in prompt engineering and practical experience with either Google Cloud's Vertex AI platform is essential for this role. You will also provide technical leadership and mentorship to other members of the AI/ML team. Key Responsibilities Lead the development and deployment of generative AI solutions utilizing LLMs, SLMs, and FMs for various applications (e.g., content generation, chatbots, summarization, code generation, etc.). Architect and implement robust and scalable infrastructure for training, fine-tuning, and serving large-scale AI models, leveraging either Vertex AI. Drive the fine-tuning and adaptation of pre-trained models using proprietary data to achieve state-of-the-art performance on specific tasks. Develop and implement effective prompt engineering strategies to elicit desired outputs and control the behavior of generative models. Manage the lifecycle of deployed models , production support, including monitoring performance, identifying areas for improvement, and implementing necessary updates or retraining. Collaborate closely with cross-functional teams (e.g., product, engineering, research) to understand business requirements and translate them into technical solutions. Provide technical leadership and mentorship to junior machine learning engineers, fostering a culture of learning and innovation. Ensure the responsible and ethical development and deployment of AI models , considering factors such as bias, fairness, and privacy. Stay up to date with latest advancements in generative AI, LLMs, and related technologies, and evaluate their potential application within the company. Document technical designs, implementation details, and deployment processes. Troubleshoot and resolve issues related to model performance and deployment. Required Skills and Experience: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Minimum of 5-8 years of hands-on experience in building, deploying, and managing machine learning models in a production environment. Demonstrable experience in managing, deploying, and fine-tuning large language models (LLMs), small language models (SLMs), and foundation models (FMs). Significant hands-on experience with prompt engineering techniques for various generative AI tasks. Proven experience working with either Google Cloud's Vertex AI platform platform . including experience with their respective model registries, deployment tools, and MLOps features. Strong programming skills in Python and experience with relevant machine learning libraries (e.g., TensorFlow, PyTorch, Transformers). Experience with cloud computing platforms (beyond Vertex AI is a plus, e.g. Azure). Solid understanding of machine learning principles, deep learning architectures, and evaluation metrics. Excellent problem-solving, analytical, and communication skills. Ability to work independently and as part of a collaborative team. Experience with MLOps practices and tools for continuous integration and continuous delivery (CI/CD) of ML models is highly desirable. Experience with version control systems (e.g., Git). Bonus Points: Experience with model governance frameworks and implementing ethical AI practices. Experience with specific generative AI use cases relevant to Logistics industry. Publications or contributions to open-source projects, technical blogs, or industry conferences are considered a plus Familiarity with data engineering pipelines and tools. Familiarity with emerging trends in generative AI, reinforcement learning from human feedback (RLHF), and federated learning approaches.

Role & responsibilities A skilled SDET with expertise in Python and a basic understanding of Generative AI (GenAI) to join our quality engineering team. The ideal candidate will be responsible for designing automated test frameworks, implementing test strategies, and leveraging AI-driven automation techniques to enhance testing efficiency. Key Responsibilities: Develop, maintain, and optimize automated test frameworks and scripts using Python . Design and execute API, UI, and performance testing using tools like Pytest, Selenium. Integrate GenAI-based automation techniques to improve test generation, defect prediction, and self-healing scripts. Collaborate with developers to implement CI/CD pipelines and ensure robust test automation in DevOps environments. Conduct root cause analysis for defects and implement intelligent test strategies for faster issue resolution. Work with large datasets and create synthetic test data using AI-based models. Leverage AI-powered tools to optimize test coverage and reduce redundant test cases. Maintain and enhance monitoring and logging frameworks for better observability in test environments. Preferred candidate profile Strong proficiency in Python for test automation and scripting. Experience with test automation tools (Pytest, Selenium, Robot Framework, Playwright). Hands-on experience in API testing (Postman, RestAssured, FastAPI, Flask). Familiarity with GenAI concepts and AI-driven testing approaches. Exposure to AI/ML libraries like TensorFlow, OpenAI API, or Hugging Face is a plus. Experience with Docker, Kubernetes, Jenkins, and Git for automation in DevOps pipelines. Working knowledge of cloud platforms ( AWS, Azure, GCP ) and infrastructure testing. Strong analytical skills with a problem-solving mindset. Good to Have: Experience with AI-powered test automation tools (Testim, Mabl, Applitools). Familiarity with LLMs (Large Language Models) and AI-assisted testing frameworks. Understanding of data science workflows for test data generation. Previous experience working in Agile/Scrum teams.

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 , 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 , 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 and on , , , and . Inviting applications for the role of Principal Consulta nt - Le ad AWS Cloud Engineer! In this role, you will own the vision, architecture, and governance of cloud infrastructure supporting scalable, secure, and high-performing AI/ GenAI platforms across the enterprise. Your mandate includes building resilient, compliant, and cost-efficient cloud ecosystems primarily on AWS, but with a strong foundation for multi-cloud operability Responsibilities Define and maintain cloud infrastructure architecture across AWS accounts, environments, and regions. Architect multi-tenants, secure VPC and networking models, supporting cross-account and hybrid integrations. Standardize Infrastructure-as-Code (Terraform) strategy for AI/ML/ GenAI workloads across teams. Govern security frameworks, including encryption, IAM boundary enforcement, secrets management, and logging. Oversee cloud automation in CI/CD pipelines and support deployment of GenAI workloads (LLM APIs, vector DBs). Design, review and implement disaster recovery, backup, and high availability strategies. Optimize cloud cost and performance with tagging, resource planning, and usage analytics. Define and support multi-cloud readiness, including network peering, SSO/SAML, and logging across clouds. Collaborate with MLOps , Compliance, InfoSec, and Architecture teams to align infrastructure with enterprise goals. Engaging in the design, development and maintenance of data pipelines for various AI use cases Active contribution to key deliverables as part of an agile development team Collaborating with others to source, analyse, test and deploy data processes Qualifications we seek in you! Minimum Qualifications hands-on AWS infrastructure experience in production environments. Experience developing, testing, and deploying data pipelines Clear and effective communication skills to interact with team members, stakeholders and end users Degree/qualification in Computer Science or a related field, or equivalent work experience Knowledge of governance and compliance policies, standards, and procedures Proven ability to manage enterprise-wide IAC, AWS CLI, and Python or Bash scripting, versioning strategy. Expert in IAM, S3, DevOps, VPC, ECS/EKS, Lambda, and serverless computing. Experience supporting AI/ML or GenAI pipelines in AWS (especially for compute and networking). Hands on experience to multi-cloud architecture basics (e.g., SSO, networking, blob exchange, shared VPC setups). Deep understanding of CI/CD automation, AI workload optimization, and infrastructure governance. Hands-on experience designing or managing infrastructure in at least one other cloud (Azure or GCP). Hands on experience to multiple AI / ML /RAG/LLM workloads and model deployment infrastructure. AWS Certified Solutions Architect - Professional or Advanced Networking Specialty. Preferred Qualifications/ Skills Experience deploying infrastructure in both AWS and another major cloud provider (Azure or GCP). Designed or migrated enterprise workloads to multi-cloud or hybrid setups. Experience with cross-cloud monitoring, networking (VPNs, Transit Gateways), and DR policies. Familiarity with multi-cloud tools (e.g., HashiCorp Vault, Kubernetes with cross-cloud clusters). Strong understanding of DevSecOps best practices and compliance requirements. In-depth exposure to regulated industries (BFSI, healthcare) requiring auditability and compliance. 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.

Hello Everyone, Optum is hiring Java Developer with AI ML flavor at Gurgaon/Noida. Primary Skills: Java, Spring, GenAI, Splunk/Dynatrace/New Relic, AWS/GCP/Azure, Deep Learning Experience: 7 yrs to 11 yrs Notice Period: Immediate to 45 days Location: Gurgaon/Noida Job Description: Experience in AI Ops that includes AI/ML Models quality monitoring and alerting, AI/ML Model development and continuous improvement, incident triage, troubleshooting, monitoring, continuous innovation Strong knowledge of GenAI models like Gemini, GPT4, and traditional machine learning models from the NLP/Deep Learning discipline. 7+ yrs of experience Java development. Hands-on experience on AI ML (Min 6 months - 1 yr in project) Experience working with data analysis (e.g., Splunk, Dynatrace, New Relic) tools. Experience working with AI technologies and cloud platforms (Google Cloud Platform, GCP). Solid incident management skills, with a data-driven and analytical approach to diagnosing complex issues Excellent problem-solving and troubleshooting skills. Ability to work collaboratively with a diverse team of engineers, architects, and developers. Ability to work independently and in a team environment Nice to Have Machine Learning certifications. Experience in a Healthcare Payer enterprise. Proficient in CRM platforms, such as Salesforce. Knowledge of data privacy regulations and practices. Experience in training team members on machine learning technologies and applications. Strong communication and project management skills. Ability to work independently and in a team environment Interested can share their updated CV at mohammad_ayub@optum.com. Thanks and Regards, Arshad Ayub - Talent Scout Optum mohammad_ayub@optum.com

Role & responsibilities Breadth of knowledge in areas of computer vision including either classical methods or ML. These areas may include Image Enhancement, SLAM, calibration, scene understanding, gaze tracking, human representation, and activity recognition. Exposure to GenAI, object detection, facial recognition, content analysis, and behavior analysis models, Experience in implementing Multi Camera Unified Intelligence use cases. Experience leveraging LLMs and developing Agentic AI modules is a good to have Candidates should have exposure to modern innovative techniques including vision transformers, foundation models, and vision-language models, with a focus on integrating these methods into resource-constrained environments. Experience in reusable /libraries, and techniques (e.g., OpenCV, TensorFlow, PyTorch) for Video Analytics Experience in optimizing and fine-tuning ISP pipelines, including tasks like noise reduction, color correction, demosaicing, and dynamic range enhancement.

Engineering Manager ( GenAI, JAVA, AI/ML, AWS,Saas is Must ) 15 years of experience in software engineering, with at least 5 years of experience in a leadership role. Strong technology expertise in Java, Microservices architecture, AWS cloud platform, AI, and the Angular framework. Solid background in building scalable and distributed systems, with expertise in technologies such as Spring boot (Spring (Core, AOP, Transactions, Data, Security), Cassandra, Kubernetes (K8s), Kafka, Docker and others. Experience with security best practices and protocols (e.g., SSL/TLS, OAuth) Hand on experience towards Architecture and Design patterns. Practice industry's leading best guidelines/processes in building enterprise products/components Proven track record of successfully leading and managing high-performing engineering teams. Excellent communication, interpersonal, and leadership skills. Ability to mentor and coach others, helping them develop their technical and leadership skills. Strong problem-solving and analytical skills. Experience with Agile development methodologies. Ability to prioritize effectively and manage multiple tasks simultaneously. Experience in building and scaling software applications. Experience in recruiting and hiring top-tier engineering talent. Ability to work effectively in a cross-functional team environment. Skills: ssl/tls,software,agile development methodologies,spring boot,kubernetes,java,security best practices,microservices architecture,agile methodologies,leadership,kafka,architecture and design patterns,ai,aws cloud platform,docker,kubernetes (k8s),aws,oauth,angular,cassandra