Senior Specialist, Data Stewardship - Innovation Lead

Merck Merck · Pharma · Telangana, India

Senior Specialist, Data Stewardship – Innovation Lead role within the EDQ&DSC team, focused on designing, building, and deploying LLM-powered automation and agentic AI solutions to transform data stewardship, improve data quality, and enable scalable governance operations in a regulated healthcare enterprise. The role involves developing AI-driven workflows, agents capable of multi-step execution, reasoning over policies, and integrating with various data platforms, while ensuring compliance, security, and responsible AI practices.

What you'd actually do

  1. Maintain a living roadmap of automation opportunities across stewardship workflows, metadata management, data quality, access/privacy, and data product operations.
  2. Design and implement automation and agentic AI systems to support data governance, enablement, and stewardship activities.
  3. Integrate automation with catalogs, lineage, data quality, R/MDM, access, and other data platforms.
  4. Package and deploy AI solutions into controlled environments, following software engineering and release management best practices.
  5. Implement logging, auditing, explainability, and versioning for AI agents, prompts, and workflows.

Skills

Required

  • 8+ years of experience in AI/ML, data science, or related domains
  • Experience building or deploying LLM-powered automation and agentic AI solutions
  • Experience with data stewardship, data quality, and data governance principles
  • Proficiency in software engineering best practices, including CI/CD, testing, and deployment
  • Understanding of responsible AI principles, including explainability, fairness, and security
  • Experience integrating AI solutions with enterprise data platforms and APIs
  • Familiarity with regulated environments and compliance requirements

Nice to have

  • Experience with specific AI frameworks and libraries (e.g., LangChain, LlamaIndex, TensorFlow, PyTorch)
  • Knowledge of cloud platforms (AWS, Azure, GCP)
  • Experience with RAG and vector databases
  • Familiarity with metadata management, data lineage, and master data management (MDM) concepts

What the JD emphasized

  • LLM-powered automation
  • agentic AI solutions
  • policy-aware AI agents
  • guardrails
  • traceability
  • auditability
  • regulated enterprise environment
  • production-grade code
  • responsible AI engineering

Other signals

  • LLM-powered automation
  • agentic AI solutions
  • data stewardship
  • data quality
  • governance operations
  • responsible AI engineering
  • policy-aware AI agents
  • guardrails
  • traceability
  • auditability