Technical Program Manager, Enterprise

Scale AI Scale AI · Data AI · New York, NY +1 · Enterprise Engineering

Technical Program Manager to own operational execution and delivery of technical work for Frontier Agent Engineering teams on enterprise customer engagements. Role involves managing timelines, milestones, risks, and dependencies, driving strategic alignment and end-to-end execution of critical Enterprise initiatives. Focus on systemic, measurable outcomes and efficiency across the agentic application development process in a high-growth AI environment.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. Risk & Dependency Mitigation: Proactively identify, track, and architect mitigations for technical risks unique to enterprise AI deployment, maintaining momentum in the face of ambiguity.
  5. Process Evolution: Modernize and scale agile execution frameworks (e.g., Jira, Linear) to support rapid, iterative machine learning and software development lifecycles.
  6. Metrics-Driven Accountability: Define, track, and report on key program health metrics, delivery forecasts, and engineering bottlenecks directly to executive leadership.

Skills

Required

  • 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.).

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.

What the JD emphasized

  • enterprise customer engagements
  • technical leadership role
  • program delivery
  • systemic, measurable outcomes
  • agentic application development process
  • hyper-growth, demanding AI environment
  • deliver reliable, high-value solutions at scale
  • enterprise-grade programs
  • frontier agents
  • enterprise AI deployment
  • machine learning and software development lifecycles
  • Generative AI lifecycle
  • LLM utilization
  • model fine-tuning
  • performance evaluation
  • executive-level stakeholders
  • complex technical challenges
  • clear business impacts
  • iterative development methodologies
  • modern project management tooling
  • modern ML/GenAI practices and infrastructure