Technical Program Manager, Enterprise
This Technical Program Manager will lead enterprise customer engagements for Frontier Agent Engineering teams, focusing on operational execution and delivery of technical work. The role involves managing timelines, milestones, risks, and dependencies across technical deliverables, driving strategic alignment and end-to-end execution of critical enterprise initiatives.
About the job
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 fine-tuning, and performance evaluation.
- Masterful Communication: Proven track record of presenting to and influencing executive-level stakeholders, with the ability to translate complex technical challenges into clear business impacts.
- Execution Excellence: Advanced proficiency with iterative development methodologies and modern project management tooling (Jira, Linear, etc.).
- Growth Mindset: An insatiable appetite for learning and deeply engaging with modern ML/GenAI practices and infrastructure.
Nice-to-Have Qualifications
- Engineering Roots: Strong software engineering fundamentals, ideally with prior professional experience as a software engineer or data developer before transitioning into program management.
- Platform Adoption Track Record: Proven success driving the internal adoption of technical platforms, SDKs, or APIs across disparate product lines or independent business units.
- Data-Centric AI Familiarity: Direct experience working with data quality pipelines, LLM-as-a-judge evaluation frameworks, or automated RLHF systems.
Compensation
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$211,200—$264,000 USD
Skills
Jira, Linear, Generative AI, LLMs, Machine Learning, Distributed Systems, Platform Services, Software Engineering, Data Quality Pipelines, RLHF
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