Job DescriptionPosition OverviewReporting to the SVP, Software Engineering and AI Operations, the Director of AI Governance & Enterprise Solutions is Momentive's senior AI subject matter expert - the person who sets the technical bar for how the company designs, builds, deploys, and governs AI agents. This role owns the Momentive Context Library, defines and enforces the standards that all AI agents must meet, leads the review and approval of agents across the portfolio, and directly builds agents and skills for the AI Operations Hub. When business units need to build AI solutions, this leader will be a strategic technical partner.
Core ResponsibilitiesContext Library Ownership- Own the Momentive Context Library - the shared knowledge repository that AI agents across the company depend on for accurate, consistent, organization-specific context.
- Define the library's architecture, taxonomy, and content standards, ensuring it is well-organized, current, and designed to be consumed reliably by agents across different use cases.
- Define and maintain the standards for centrally-owned content - shared company knowledge, cross-functional reference material, and foundational context that spans business units - ensuring it remains accurate, current, and consistently structured.
- Partner with AI Operations Hub spoke leads to help them build, structure, and maintain department-owned content - including converting existing documentation and institutional knowledge into library-ready context.
Agent Review & Standards- Define the technical review criteria and quality standards that all AI agents, skills, and connectors must meet for AI Operations Hub approval - covering design, architecture, data handling, accuracy, safety, and operational readiness.
- Lead the technical review and approval process for all AI agents submitted through the AI Operations Hub intake process, making or formally endorsing go/no-go recommendations.
- Develop agent development guidelines, design patterns, and templates that translate AI Operations Hub standards into practical, reusable building blocks for spoke teams.
- Identify systemic quality issues, common failure modes, and emerging risks across the agent portfolio, and use those insights to continuously raise the technical bar.
Building for AI Operations- Directly design and build AI agents, skills, and connectors for the AI Operations team's own use - including tooling that supports AI Operations Hub functions like intake review, registry management, and performance monitoring.
- Prototype and evaluate new agent architectures, orchestration frameworks, and tooling approaches before recommending them for broader organizational use.
Technical Consulting & Deployment Guidance- Serve as the primary technical advisor to spoke teams as they design and build AI solutions - providing hands-on architecture guidance, reviewing approach before build begins, and troubleshooting when things go wrong.
- Own the AI Operations Hub's standards for how agents are deployed, monitored, and secured in production - including environment configuration, observability requirements, access controls, and incident response protocols.
- Partner with Corporate IT on the platform and infrastructure decisions that affect how agents are deployed and maintained across the organization.
- Assess and recommend AI platforms, tools, and vendor solutions as the technology landscape evolves, with a focus on what will actually serve Momentive's operational model.
- Partner on how AI agents and automation intersect with the enterprise application portfolio - aligning platform strategy, tooling investments, and governance standards across both functions.
Enablement- Develop technical reference materials, design pattern libraries, and decision guides that help spoke teams make better architectural choices independently.
- Deliver targeted technical training and workshops when spoke teams need to build a foundational capability - this is a supporting function, not a primary one.
- Actively connect spoke teams to each other - surfacing shared use cases, reusable patterns, and prior work across business units so teams build on each other's progress instead of solving the same problems independently.
- Other duties as assigned.
Qualifications- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent work experience.
- 7+ years of hands-on experience designing and building software or AI systems, with at least 3 years working directly with large language models, AI agents, and production AI deployments.
- Deep practical expertise with AI agent architectures, LLM APIs, orchestration frameworks (LangChain, LlamaIndex, CrewAI, AutoGen, or similar), and the tradeoffs between them.
- Expert-level knowledge of prompt engineering, retrieval-augmented generation (RAG), tool use and function calling, context window management, and agent evaluation methodologies.
- Demonstrated experience building and deploying AI agents in production environments - including decisions around deployment architecture, observability, access controls, and failure handling.
- Experience designing or governing shared knowledge repositories, context management systems, or information architectures for AI systems.
- Strong instincts for AI risk - understanding where agents fail, how to test for it, and how to build systems that degrade gracefully.
- Experience with enterprise AI platforms such as Claude Enterprise, Azure OpenAI Service, Google Vertex AI, or similar.
- Strong written and verbal communication skills - able to make complex technical positions clear and defensible to both engineering and non-technical leadership audiences.
- Familiarity with AI governance frameworks (NIST AI RMF or similar) and responsible AI principles as they apply to production systems.
- Experience operating in a cross-functional environment where you set standards others must follow, not just your own team.
- Demonstrated growth mindset and commitment to staying ahead in a rapidly evolving field.
What Success Looks Like- Every AI agent that reaches production has been reviewed against a clear, defensible technical standard - and the review process makes agents better, not just slower.
- The Momentive Context Library is the most trusted source of organizational knowledge available to AI agents - current, well-structured, and actively relied upon by spoke teams.
- AI Operations' own agents are high-quality, well-maintained, and set the standard that spoke teams aspire to.
- Spoke teams leave technical consultations with a clearer path forward and better architectural decisions than they would have made on their own.
- Production agents are deployed consistently, monitored reliably, and secured according to a clear, documented standard.
- The AI Operation's Hub technical bar is high and rising - and the organization's AI portfolio reflects it.
- New capabilities are evaluated and piloted by the AI Operations Hub before spoke teams start asking for them.
Medical, Dental & Vision Benefits
401(k) Savings Plan with Company Match
Flexible Planned Paid Time Off
Generous Sick Leave
Inclusive & Welcoming Environment
Purpose-Driven Culture
Work-Life Balance
Commitment to Community Involvement
Employer-Paid Parental Leave
Employer-Paid Short-Term Disability
Remote Work Flexibility
