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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.
Job Responsibility
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
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
Risk & Dependency Mitigation: Proactively identify, track, and architect mitigations for technical risks unique to enterprise AI deployment
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
Requirements
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
2+ years of dedicated experience managing programs focused directly on core engineering infrastructure, platform services, or distributed systems
Strong foundational understanding of the Generative AI lifecycle, including LLM utilization for structured downstream tasks, model fine-tuning, and performance evaluation
Proven track record of presenting to and influencing executive-level stakeholders, with the ability to translate complex technical challenges into clear business impacts
Advanced proficiency with iterative development methodologies and modern project management tooling (Jira, Linear, etc.)
An insatiable appetite for learning and deeply engaging with modern ML/GenAI practices and infrastructure
Nice to have
Strong software engineering fundamentals, ideally with prior professional experience as a software engineer or data developer before transitioning into program management
Proven success driving the internal adoption of technical platforms, SDKs, or APIs across disparate product lines or independent business units
Direct experience working with data quality pipelines, LLM-as-a-judge evaluation frameworks, or automated RLHF systems