Assoc. Dir, Agentic Standards & Context Intelligence

Merck; North Wales (Montgomery County); Hybrid; USD 173,000 - 273,000; Full time

Benefits offered by this job

Hybrid work model

Healthcare benefits

401(k) plan

Paid holidays

Vacation days

Job summary

Merck is leading a GenAI & Agentic Center of Excellence to define standards, shared context foundations, and reusable patterns for enterprise-grade AI agents across the commercial portfolio. The role focuses on standards governance, context engineering, and cross‑functional collaboration to scale AI responsibly and effectively.

The candidate will lead a team of experts, drive adoption of best practices, and align initiatives with enterprise architecture and data governance.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, IT, or related STEM field.
• Experience defining and driving adoption of technical standards, playbooks, or frameworks in a large, matrixed organization
• Hands‑on understanding of the GenAI agent lifecycle (design, deploy, monitor, improve), including retrieval‑augmented generation, tool use, orchestration, evaluation, and guardrails
• Experience with context engineering concepts applied to AI systems — grounding, retrieval strategy, semantic definitions, or shared context layers
• Experience influencing senior stakeholders across engineering, data, product, and enterprise governance functions

Responsibilities

• Define and evolve standards playbooks and specs across the full agent lifecycle.
• Own the shared context layer including ontology and knowledge graph.
• Elevate context handling as a measurable platform component.
• Drive adoption of agentic standards across teams with enablement content.
• Align CoE standards with enterprise architecture, data, and governance.
• Partner with cross-functional teams to translate standards into reusable patterns.
• Establish metrics for adoption, context quality, and business impact.
• Lead and scale a team of standards authorship and context engineers.

Skills

Agentic AI Standards

AI Governance

AI Playbook Development

Change Management

Context Engineering

Cross-Functional Collaboration

Generative AI (GenAI)

Governance Frameworks

Knowledge Graphs & Ontology

LLMs

Multi-Agent Systems

People Leadership

Program Management

Responsible AI

Retrieval-Augmented Generation (RAG)

Semantic Layer Design

Stakeholder Relationship Management

Standards Adoption

Strategic Communications

Technical Leadership

Access-Aware Retrieval

Agent Evaluation

Agent Observability

Business Glossary & Metric Registry

Context Health Metrics

Data Governance for AI

Enterprise Architecture Influence

MLOps / LLMOps

Prompt Engineering Libraries

Regulated-Industry AI Experience

Education

Bachelor's degree in Computer Science, Data Science, Engineering, Information Technology, or related STEM field

Job description

Job Description

Generative and agentic AI are reshaping how commercial teams work — from how insights are surfaced, to how content is created and reviewed, to how decisions are made in market. To move at the speed of that opportunity without compromising on trust, compliance, or quality, the Human Health Division is scaling a GenAI & Agentic Center of Excellence: the team that defines the standards, reusable frameworks, and shared context foundations used to build, evaluate, and ship enterprise‑grade AI agents across the commercial portfolio. As adoption expands across therapeutic areas, business units, and international markets, two things determine whether agents scale well: an opinionated, well‑governed rulebook that every agent team can start from, and a shared context foundation so that agents reason with consistent business meaning rather than re‑interpreting raw data differently each time. Standards without context produce compliant but analytically wrong agents; context without standards produces inconsistency at scale.

Primary Responsibilities Include:

• Standards vision and roadmap: Defining and evolving playbooks, specifications, and technical standards across the full agent lifecycle (design, deploy, monitor, improve), and driving them from research‑backed drafts through use‑case‑validated versions.
• Context intelligence strategy: Owning the strategy for the shared, governed context layer — ontology, knowledge graph, semantic definitions, metric registries, and business glossary — so agents reason with consistent commercial meaning (brands, channels, vendors, KPIs) rather than raw table lookups.
• Context as infrastructure: Elevating context handling to a first‑class, measurable component of the platform, with instrumentation, lifecycle controls, versioning, and health metrics (accuracy, freshness, compliance) that make context quality continuously measurable and improvable at scale.
• Standards adoption and enablement: Driving socialization and adoption of agentic standards and context patterns across business, CoE, and platform teams through enablement content, starter kits, reference patterns, and developer‑facing integrations.
• Enterprise alignment: Aligning CoE standards and context approaches with broader enterprise architecture, data, and governance functions — clarifying CoE vs. enterprise responsibilities and influencing enterprise‑level standards.
• Cross‑pillar partnership: Partnering with responsible‑AI, governance, engagement, and platform teams to translate standards and context capabilities into reusable delivery patterns and operational practices.
• Measurement and continuous improvement: Establishing metrics for standards adoption, context quality, and business impact, and running feedback loops that translate developer and business input into standards and context revisions.
• Team leadership: Leading, coaching, and scaling a team of technical specialists across standards authorship, context engineering, and adoption.

Basic Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, Information Technology, or a related STEM field
• Experience defining and driving adoption of technical standards, playbooks, or frameworks in a large, matrixed organization
• Hands‑on understanding of the GenAI agent lifecycle (design, deploy, monitor, improve), including retrieval‑augmented generation, tool use, orchestration, evaluation, and guardrails
• Experience with context engineering concepts applied to AI systems — grounding, retrieval strategy, semantic definitions, or shared context layers
• Experience influencing senior stakeholders across engineering, data, product, and enterprise governance functions

Preferred Qualifications

• Experience in a regulated industry (pharmaceutical, healthcare, financial services) with audit and compliance obligations
• Experience designing or governing ontology, knowledge graph, semantic layer, business glossary, or metric registry capabilities for analytics or AI consumption
• Experience instrumenting context or data quality metrics (accuracy, freshness, compliance, lineage) as measurable platform health signals
• Experience with evaluation‑driven and specification‑driven development practices for AI agents
• Experience standing up or scaling an AI center of excellence, platform governance function, or standards program with measurable adoption outcomes
• Experience leading and mentoring a technical team spanning standards and data/context disciplines

Required Skills

• Agentic AI Standards
• AI Governance
• AI Playbook Development
• Change Management
• Context Engineering
• Cross‑Functional Collaboration
• Generative AI (GenAI)
• Governance Frameworks
• Knowledge Graphs & Ontology
• Large Language Models (LLMs)
• Multi‑Agent Systems
• People Leadership
• Program Management
• Responsible AI
• Retrieval‑Augmented Generation (RAG)
• Semantic Layer Design
• Stakeholder Relationship Management
• Standards Adoption
• Strategic Communications
• Technical Leadership
• Access‑Aware Retrieval
• Agent Evaluation
• Agent Observability
• Business Glossary & Metric Registry Design
• Context Health Metrics (Accuracy, Freshness, Compliance)
• Data Governance for AI
• Enterprise Architecture Influence
• MLOps / LLMOps
• Prompt Engineering Libraries
• Regulated‑Industry AI Experience

Required Skills

• Business Informatics
• Business Insights
• Business Intelligence (BI)
• Business Metrics
• Computer Science
• Content Development
• Content Management
• Content Marketing
• Database Design
• Data Engineering
• Data Modeling
• Data Science
• Data Visualization
• Design for Maintainability
• Developer Tools
• Engineering Leadership
• First Order Logic
• Life Cycle Planning
• Machine Learning (ML)
• Progress Monitoring
• Software Agent
• Software Development
• Stakeholder Relationship Management
• Standards Compliance + 3 more

Preferred Skills

• Access‑Aware Retrieval
• Agent Evaluation
• Agent Observability
• Business Glossary & Metric Registry Design
• Context Health Metrics (Accuracy, Freshness, Compliance)
• Data Governance for AI
• Enterprise Architecture Influence
• MLOps / LLMOps
• Prompt Engineering Libraries
• Regulated‑Industry AI Experience

US And Puerto Rico Residents Only

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.

San Francisco Residents Only

We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only

We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance

Search Firm Representatives Please Read Carefully

Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre‑existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Employee Status

Regular

Relocation

No relocation

VISA Sponsorship

No

Travel Requirements

10%

Flexible Work Arrangements

Hybrid

Shift

Not Indicated

Valid Driving License

No

Hazardous Material(s)

n/a

Job Posting End Date

• A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.

Requisition ID

R419112

Salary Range

$173,200.00 - $272,600.00

We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.

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We offer a comprehensive package of benefits. Available benefits include 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. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.