Key Responsibilities:Agent Development & Architecture:Build agentic workflows using LangChain/LangGraph and similar frameworks.
- Develop autonomous agents for data validation, reporting, document processing, and domain workflowsDeploy scalable, resilient agent pipelines with monitoring and evaluationGenAI Application EngineeringDevelop GenAI applications using models like GPT, Gemini, and LLaMImplement RAG, vector search, prompt orchestration, and model evaluationPartner with data scientists to productionize POCsData & Platform EngineeringBuild distributed data pipelines (Python, PySpark)Develop APIs, SDKs, and integration layers for AI-powered applicationsOptimize systems for performance and scalability across cloud/hybrid environments.MLOps / LLMOpsContribute to CI/CD workflows for AI models-deployment, testing, monitoringImplement governance, guardrails, and reusable GenAI frameworks.Collaboration & Stakeholder EngagementWork with analytics, product,



and engineering teams to define and deliver AI solutionsParticipate in architecture reviews and iterative development cyclesSupport knowledge sharing and internal GenAI capability building.Key Requirements:8-12 years of experience in AI/ML engineering, data science, or software engineering, with atleast 2 years focused on GenAIStrong programming expertise in Python, distributed computing using PySpark, and API developmentHands on experience with LLM frameworks (LangChain, LangGraph, Transformers, OpenAI/Vertex/Bedrock SDKs)Experience developing AI agents, retrieval pipelines, tool calling structures, or autonomous task orchestrationSolid understanding of GenAI concepts: prompting, embeddings, RAG, evaluation metrics, hallucination identification, model selection, fine tuning, context engineeringExperience with cloud platforms (Azure/AWS/GCP), containerization (Docker), and CI/CD pipelines for ML/AIStrong problem solving, system design thinking, and ability to translate business needs into scalable AI solutionsExcellent verbal, written communication and presentation skills. Valuable to HaveExperience in workflow automation and building reusable AI componentsBackground in analytics, statistical models, or enterprise data productsExperience with MLOps / LLMOps tooling

📌 Data Scientist (Chennai)
🏢 Dun & Bradstreet India
📍 Chennai