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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Architect, Data Context Layer - **Company:** Merck Sharp & Dohme LLC - **Location:** North Wales, PA, United States - **Experience:** Expert - **Salary:** $142,400.0 - $224,100.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computing Platforms, Continuous Integration, Data Architecture, Data Governance, Digital Architecture, Graph Database, Identity and Access Management, Interoperability, Metadata, Meta-Data Management, Web Ontology Language, Resource Description Framework (RDF), Release Management, Requirements Management, Semantic Web, Systems Integration, AI Infrastructure, Enterprise Data Management, Prompt Engineering, Data Management, Virtual Agents - **Published:** July 6, 2026 - **Apply:** https://www.juju.com/job/00000000geb7vw ## About the Role The ideal candidate has deep experience in enterprise architecture, data platforms, semantic technologies, and AI-enabled systems. Familiarity with **ontologies, OWL, metadata-driven architectures, agentic AI, prompt engineering, and context engineering** is required, as the platform must support both human and AI-driven consumers of context., + Bachelors degree + 8+ years of experience in enterprise architecture, solution architecture, data architecture, or platform architecture. + Strong technical background in data platforms, metadata systems, semantic technologies, or AI infrastructure. + Familiarity with **ontologies, OWL, RDF, knowledge graphs, and semantic layer concepts** . + Experience designing platforms that support self-service, enterprise-scale reuse, and governed access. + Expertise in **agentic AI, prompt engineering, and context engineering** concepts. + Experience defining and enforcing technical standards across multiple teams. + Strong ability to communicate architecture decisions to both technical and non-technical stakeholders. Preferred Qualifications + Experience with MCP, A2A, Timbr, or similar context-serving or semantic interoperability technologies. + Background in enterprise data governance, metadata management, or data catalog architectures. + Experience supporting AI-enabled platforms or agentic workflows. + Knowledge of production concerns such as observability, testing, CI/CD, identity and access management, and lifecycle management. + Experience creating reference architectures and reusable patterns for platform teams. + Familiarity with regulated or security-sensitive enterprise environments., Context Mapping, Data Modeling, Design Applications, Enterprise Architecture (EA), Enterprise Architecture Management, Enterprise Data, Enterprise Data Management, Enterprise Security Operations, Metadata, Metadata Management, Ontology, Prompt Engineering, Reference Architectures, Release Management, Requirements Management, Semantic Web, Solution Architecture, System Designs, System Integration ## Description This role is part of a broader enterprise initiative to establish a **Data Context Layer (DCL)** - a foundational capability designed to provide consistent, reusable, and scalable context across enterprise data products. The DCL is intended to address challenges related to **data fragmentation, lack of shared semantics, and inconsistent interpretation of data across systems and products** . It establishes a unified layer for representing context, relationships, and meaning, enabling downstream products to operate with greater consistency, interoperability, and intelligence. In addition, the DCL plays a critical role in enabling **agentic AI capabilities across the enterprise** by providing the structured context and semantic grounding required for intelligent agents to operate reliably. This includes ensuring that agent-driven workflows and decisions are based on **consistent, governed, and interpretable data context** , reducing risks associated with fragmentation, ambiguity, and lack of control. Within this initiative, we are seeking a Lead Architect to define and guide the conceptual and technical architecture for an enterprise platform that enables teams to **publish, discover, and consume standardized data context through self-service** . This role will shape the target architecture, integration patterns, and technical standards that support scalable, secure, and production-ready context services across the enterprise., + Define the target architecture for the enterprise data context self-service platform., + Design architecture that supports both self-service user workflows and AI/agentic consumption patterns. + Ensure context can move from development to production in a governed, scalable, and supportable way. + Define non-functional requirements including performance, resilience, security, compliance, and operational maintainability. + Review solution designs and implementation plans to ensure adherence to architectural standards. + Create reference architectures, patterns, and decision records to guide implementation teams. + Collaborate with platform teams to support long-term scalability, reuse, and interoperability across domains. + Help shape how the platform supports **agentic AI workflows** , including structured prompt context, tool access, and reliable data grounding. ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Guiding Agentic AI with Vue](https://www.wearedevelopers.com/videos/2033-guiding-agentic-ai-with-vue) - [WebMCP - Making Agents a First-Class Citizen of the Web - Andre Cipriani Bandarra & François Beaufort](https://www.wearedevelopers.com/videos/1811-webmcp-making-agents-a-first-class-citizen-of-the-web-andre-cipriani-bandarra-francois-beaufort) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [AI in Leadership: How Technology is Reshaping Executive Roles](https://www.wearedevelopers.com/videos/1705-ai-in-leadership-how-technology-is-reshaping-executive-roles) - [GraphQL Mesh – Why GraphQL between services is the worst idea and the best idea at the same time!](https://www.wearedevelopers.com/videos/9-graphql-mesh-why-graphql-between-services-is-the-worst-idea-and-the-best-idea-at-the-same-time) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [What Makes WeAreDevelopers World Congress Different From Every Other Tech Event?](https://www.wearedevelopers.com/magazine/701-what-makes-wearedevelopers-world-congress-different-from-every-other-tech-event) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers)