Senior Analyst - Data Quality

Job Title: Senior Analyst - Data Quality

Function: Digital Innovation & Technology

Location: Powai, Mumbai

Overview
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 Responsibilities1.

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 recall@k and precision@k.
+ Use LangSmith for tracing, automated evaluations, regression testing, and continuous system-level quality monitoring.

2.

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.

3.

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

4.

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.

5.

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.

6.

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 standa...