Sr Analyst - Data Quality

Job highlights

• Bachelors or Masters degree in Computer Science,Artificial Intelligence,Data Science,Statistics,Mathematics,Engineering,or a related discipline
• Build interpretable models where required. . Engineering Integration Collaborate with backend engineering teams to seamlessly integrate agentic and GenAI systems into production applications
• Preferred Experience

Job Summary

Job Title: Senior Analyst - Data Quality

Function: Digital Innovation Technology

Location: Mumbai

This role demand strong GenAI experience, emerging mastery in Agentic AI Systems, and a good foundation in classical ML. You will design and build intelligent, tool-using agents, multi-agent systems, RAG pipelines, and LLM-based applications leveraging the LangChain, LangGraph ecosystem, LangSmith for evaluation.

Key Responsibilities

• GenAI / LLM Application Development Build GenAI applications using: LangChain and LangGraph Implement RAG architectures with: Retrieval, reranking, chunking, and memory strategies Vector databases such as FAISS, Azure AI Search, OpenSearch, and pgvector Design prompt-engineering strategies: Instruction following ReAct (Reasoning + Acting) Chain-of-thought structuring Self-reflection and planning loops Evaluation strategy: Implement evaluation frameworks for classical ML and GenAI systems, covering statistical validation, reliability, and robustness. Assess LLM outputs, RAG pipelines, and agent workflows for grounding quality, relevance, and retrieval accuracy, such as EMAIL_ADDRESS and EMAIL_ADDRESS. Use LangSmith for tracing, automated evaluations, regression testing, and continuous system-level quality monitoring.
• Agentic System Architecture Build agentic workflows: Tool-calling agents Planner-executor systems Multi-agent communication systems Hierarchical agent architectures Deep agents Integrate memory systems: Episodic memory Semantic memory Vector-based long-term knowledge Implement evaluation frameworks for agentic systems using LangSmith.
• Model Context Protocol (MCP) Tooling Implement MCP servers for external tool connectivity. Build tools that allow agents to interact with: APIs Code-execution environments Knowledge bases Company applications
• Classical ML (Foundational DS Skills) Apply ML models to structured and unstructured data. Conduct feature engineering, model selection, and hyperparameter tuning. Build interpretable models where required.
• Engineering Integration Collaborate with backend engineering teams to seamlessly integrate agentic and GenAI systems into production applications. Implement observability, tracing, and monitoring for GenAI workflows using LangSmith to ensure reliability and system-level transparency.
• Cloud MLOps Quality Monitor ML modelling performance, data drift, concept drift, and model quality. Apply hands-on experience across AWS, Azure, or Databricks, with flexibility to work on any cloud platform. Adhere to stringent quality assurance and documentation standards using version control and code repositories, such as Git, GitHub, and Markdown.

Education and Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related discipline. Relevant GenAI, ML, cloud, Databricks, or MLOps certifications are desirable.

Preferred Experience

• Enterprise deployment of complex multi-agent or multimodal LLM solutions. Knowledge of Responsible AI, model governance, data privacy, security, and auditability. AI or analytics delivery experience in manufacturing, supply chain, sales, service, channel operations, or digital transformation.

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