About this role
As a Technical Program Manager , you will partner with our Frontier Agent Engineering teams on enterprise customer engagements — owning operational execution and delivery of our technical work by managing timelines, milestones, risks, and dependencies across technical deliverables. You will drive the strategic alignment and end-to-end execution of our most critical Enterprise initiatives. This is a high-leverage, technical leadership role where you will own program delivery from initial scoping to measurable, enterprise-wide adoption. You will serve as the core communication backbone and connective tissue between engineering, product, and executive leadership.
You are not just managing timelines; you are accountable for systemic, measurable outcomes, driving efficiency across the full agentic application development process. Operating in a hyper-growth, demanding AI environment, you will translate technical complexity into clear execution strategies, proactively mitigate risks, and ensure our engineering teams deliver reliable, high-value solutions at scale.
Key Responsibilities
• End-to-End Program Ownership: Own the strategic planning, scheduling, and high-velocity execution of multiple enterprise-grade programs, ensuring on-time delivery against aggressive product goals. Run weekly cross-functional syncs, surface blockers, drive decisions.
• Cross-Functional Architecture Integration: Manage complex dependencies and technical communication across core teams (e.g., Platform, Forward Deployed Engineering, Product) to seamlessly deliver frontier agents to our enterprise customers.
• Technical Translation & Executive Influence: Synthesize deep technical complexities into concise, actionable insights for both engineers and C-suite stakeholders. Drive absolute clarity across the delivery team regarding priorities, risks, and strategic outcomes.
• Risk & Dependency Mitigation: Proactively identify, track, and architect mitigations for technical risks unique to enterprise AI deployment, maintaining momentum in the face of ambiguity.
• Process Evolution: Modernize and scale agile execution frameworks (e.g., Jira, Linear) to support rapid, iterative machine learning and software development lifecycles.
• Metrics-Driven Accountability: Define, track, and report on key program health metrics, delivery forecasts, and engineering bottlenecks directly to executive leadership.
Minimum Qualifications
• 5+ Enterprise-Scale Experience: 5+ years of experience as a Technical Program Manager or in a technical leadership role managing complex, large-scale software engineering or machine learning development projects.
• Engineering Domain Expertise: 2+ years of dedicated experience managing programs focused directly on core engineering infrastructure, platform services, or distributed systems.
• AI/ML Literacy: Strong foundational understanding of the Generative AI lifecycle, including LLM utilization for structured downstream tasks, model