Lead Architect, Data Context Layer

MSD

Lead Architect designing an enterprise platform for data context self-service. Ensuring consistency and governance in AI-enabled workflows and enterprise data integration.

Posted 7/6/2026full-timeRahway • New Jersey, Pennsylvania • 🇺🇸 United StatesSenior💰 $142,400 - $224,100 per yearWebsite

About the role

Key responsibilities & impact

Define the target architecture for the enterprise data context self-service platform.
Establish architectural standards and patterns for: context publishing discovery access control versioning validation lineage and provenance observability and monitoring
Partner with product, engineering, service design, security, and governance teams to ensure the platform is technically sound and aligned to enterprise needs.
Evaluate and recommend technologies and integration patterns including: ontology and semantic modeling approaches OWL/RDF-based systems knowledge graphs semantic layers MCP, A2A, and Timbr-like technologies where applicable
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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

medical, dental, vision healthcare and other insurance benefits (for employee and family)
retirement benefits, including 401(k)
paid holidays, vacation, and compassionate and sick days.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data PlatformsMetadata SystemsOntology ModelingOWLRDFKnowledge GraphsSemantic Layer ConceptsContext EngineeringPrompt EngineeringNon-Functional Requirements Definition

Soft Skills

CommunicationCollaboration

Certifications

Bachelor's Degree