Senior Technical Architect , Data Context Layer

Merck Merck · Pharma · Telangana, India

Senior Technical Architect to design and implement an enterprise Data Context Layer (DCL) platform. This platform will provide consistent, reusable context across enterprise data products, addressing data fragmentation and lack of shared semantics. A key function is enabling agentic AI capabilities by providing structured context and semantic grounding for intelligent agents, supporting agent-driven workflows and decisions. The role requires hands-on experience in platform architecture, data systems, semantic technologies (ontologies, OWL, RDF, knowledge graphs), and AI-enabled workflows, including agentic AI, prompt engineering, and context engineering.

What you'd actually do

  1. Design and implement technical architecture patterns for the enterprise data context self-service platform.
  2. Define solution-level technical approaches for: context publishing, discovery, access control, versioning, validation, lineage and provenance, monitoring and observability
  3. Collaborate with product, lead architecture, engineering, service design, security, and governance teams to turn platform requirements into implementable designs.
  4. Develop technical standards and reference implementations that can be reused by delivery teams.
  5. Evaluate and integrate enabling technologies such as: ontology and semantic modeling approaches, OWL/RDF stacks, knowledge graphs, semantic layers, MCP, A2A, and timbr-like technologies where relevant.

Skills

Required

  • 7+ years of experience in technical architecture, solution architecture, data architecture, or senior engineering roles.
  • Strong hands-on experience with data platforms, APIs, distributed systems, or platform engineering.
  • Familiarity with ontologies, OWL, RDF, knowledge graphs, and semantic layer concepts.
  • Experience designing and implementing scalable, secure, production-grade platform capabilities.
  • Working knowledge of agentic AI, prompt engineering, and context engineering concepts.
  • Ability to translate architecture requirements into practical technical designs and implementation patterns.
  • Strong problem-solving skills and experience working closely with engineering teams.

Nice to have

  • Experience with MCP, A2A, timbr, or similar context-serving or semantic interoperability technologies.
  • Background in enterprise metadata management, data governance, or knowledge platform design.
  • Experience supporting AI-enabled platforms.

What the JD emphasized

  • agentic AI capabilities
  • agent-driven workflows
  • structured context and semantic grounding
  • consistent, governed, and interpretable data context
  • agentic AI, prompt engineering, and context engineering

Other signals

  • enabling agentic AI capabilities
  • structured context and semantic grounding for intelligent agents
  • agent-driven workflows and decisions
  • support both human and AI consumers of context
  • agentic AI workflows, including structured prompt context, tool access, and reliable grounding data