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# Director, Technical Program Management - Meta Business AI

- **Company:** The Meta Game, Inc.
- **Location:** Menlo Park, CA, United States
- **Experience:** Expert
- **Salary:** $245,000.0 - $309,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Systems Engineering, Software Product Management, Software Engineering, AI Infrastructure, Large Language Models
- **Published:** August 22, 2026
- **Apply:** https://dejobs.org/x/x/90E57EACFC83491A8AA8ACF438AC2DE6/job/

## About the Role

decisions.The ideal candidate is a proven TPM leader with a technical background in infrastructure, systems, or software engineering, an effective cross-organization collaborator, and an effective communicator who can distill complex technical topics for both technical and executive audiences. They have experience navigating ambiguity, defining structure in evolving problem spaces, and delivering results in rapidly changing product areas; they are skilled at leading a team, developing and driving high-level strategy, and - equally - personally executing on critical workstreams, including technical analysis, program planning, and stakeholder coordination. They can sift through complex information, distill key insights, and elevate critical data to drive informed decisions at every level, from the working team to senior leadership., 9. 15+ years of experience in technical program management, software engineering, or systems engineering, with demonstrated progression into organizational leadership

 10. 8+ years of experience managing people managers and leading organizations of technical program managers or engineers across multiple concurrent, large-scale programs
 11. Experience driving execution strategy across multiple engineering organizations simultaneously, including defining program management frameworks and operating models at scale
 12. Experience partnering with executive and senior engineering leadership to shape organizational strategy, influence technical roadmaps, and drive cross-functional alignment
 13. Experience building and scaling high-performing technical organizations, including attracting talent, developing leadership pipelines, and managing organizational health through periods of significant growth or change, 14. Familiarity with how GenAI / LLM workloads drive infrastructure demand, cost, and capacity
 15. Experience with capacity and cost economics, including infrastructure cost modeling, unit economics, and ROI analysis
 16. Experience owning executive communications and decision frameworks for large, cross-functional technical programs
 17. Experience in Business AI, ads, or AI-agent / agentic-commerce domains

## Description

Meta Business AI is one of the company's fastest-growing AI product areas - AI agents that help businesses connect with their customers. As this product scales rapidly toward serving businesses and conversations at massive scale, delivering that experience reliably and efficiently - and making the right tradeoffs at speed - is mission-critical. We are hiring a Director of Technical Program Management to own that mandate and to lead the small, senior team that drives it.This is a hands-on, player-coach role. The right leader directly manages a small, highly senior team of technical program managers while personally owning the most complex, highest-leverage programs themselves. They set the technical and execution bar for how fast, how good, how efficient, and how reliable the product is, and they build the analytical and communication backbone that enables Engineering, Data Science, Product, and leadership to make the right performance, efficiency, quality, cost, and capacity, 1. Directly lead, mentor, and grow a small, senior team of technical program managers, setting direction and standards while remaining hands-on with the most critical programs

 2. Personally own the highest-leverage, most complex programs end-to-end - leading technical discussions, driving execution, and delivering results, not only managing through others
 3. Define and lead the technical execution strategy for AI infrastructure and capacity across the product area - performance, efficiency, quality, reliability, and capacity
 4. Build the decision-making backbone - models, scorecards, and frameworks - that makes performance/efficiency/quality/cost/capacity tradeoffs explicit and enables faster, better-grounded cross-functional and leadership decisions
 5. Partner with Engineering and Product leadership to define and revise the long-term strategy for the area, aligning roadmaps, instrumentation, and priorities across teams
 6. Keep the organization and senior leadership informed on progress: set milestones, communicate program status, surface risks early, and drive escalations to resolution
 7. Work across organizations to align plans, manage dependencies, drive execution, and deliver broad solutions through influence, not authority
 8. Own people management for the team - hiring, coaching, career growth, performance, and team culture - while keeping the team small, senior, and high-leverage


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