About the role
As the Technical Program Manager for AI Platform, you’ll turn our internal AI components and platform foundations into golden paths for the Product & Tech teams shipping AI experiences to customers. You’ll align roadmaps on shared components, establish clear owners, and make platform leverage visible through metrics and reporting.
You Will- Own the shared-foundations program. Maintain the view of components that multiple feature teams need (agent handoff, identity, context, memory, governance, and more). Drive a single accountable owner, clear roles, and decision dates for each, overlaying team roadmaps without replacing them.
- Drive cross-team decisions to closure. Frame the decisions that unblock architecture, sequence product, UX, and engineering inputs, and run working sessions with named owners and dated action items.
- Scale an innersource model. Partner with engineering to establish a contribution-based approach for shared AI components: versioned templates, reference implementations, and docs that anyone can improve through review, with clear guidelines, release processes, and safe staged rollout.
- Report on platform scorecard. Define metrics that capture ecosystem leverage, adoption, quality, and team velocity. Set baselines and targets, secure instrumentation, and bring the results into leadership and stakeholder reporting.
- Reduce duplication. Identify capabilities built in multiple places and drive consolidation/unification, tracking those migration plans across teams.
- Partner on governance. Work with security, identity, audit, and legal teams to continually iterate and track responsible AI requirements within the platform.
- Communicate clearly. Write decision-first updates tailored to leaders and project stakeholders.
- 2-4 years of technical program management on platform, infrastructure, or developer-experience programs spanning many teams and timezones.
- Fluency in LLM & agent systems: orchestration, tool use, MCP, memory, context, evals.
- Experience defining platform or developer metrics: baselines, targets, instrumentation, and adoption measures. You’ve made invisible infrastructure work visible to leadership.
- Experience enabling shared components through SDK-style or innersource models, including versioning and release management.
- Proven ability to lead without authority across engineering, product, UX, and security.
- Strong planning discipline: dependency mapping, risk tracking, capacity awareness.
- Excellent written communication, especially decision memos and executive reporting.
- Legally eligible and available to work a hybrid schedule in BLR office.
- Fluency in English is required.
Nice to have
- Familiarity with agent interoperability protocols and data platform governance tooling.
- Experience consolidating internal systems and managing build/buy/adopt decisions.
- Familiarity with AI governance, agent identity, auditing, and compliance.
- Experience with Jira, Confluence, GitLab, and work-management tools at scale.