Technical Program Manager, Enterprise

Scale; Greater London; On-site; GBP 120,000 - 150,000; Full time

Job summary

Scale is seeking a Technical Program Manager to partner with Frontier Agent Engineering on enterprise customer engagements, owning execution from scoping to enterprise-wide adoption. You will drive alignment across engineering, product, and leadership in a hyper-growth AI environment, translating complexity into clear delivery strategies and mitigating risks to ensure high-value solutions at scale.

The role emphasizes end-to-end program ownership, cross-functional architecture integration, and

Qualifications

• 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.

Responsibilities

• End-to-End Program Ownership: Strategic planning, scheduling, and high-velocity execution of multiple enterprise-grade programs; run weekly cross-functional syncs and surface blockers.
• Cross-Functional Architecture Integration: Manage dependencies and technical communication across core teams to deliver frontier agents to enterprise customers.
• Technical Translation & Executive Influence: Translate deep technical complexities into concise, actionable insights for engineers and executives; clarify priorities and risks.
• Risk & Dependency Mitigation: Identify, track, and mitigate technical risks in enterprise AI deployment while maintaining momentum.
• Process Evolution: Modernize and scale agile execution frameworks to support ML and software lifecycles.
• Metrics-Driven Accountability: Define, track and report program health metrics and delivery forecasts to leadership.

Skills

Enterprise-Scale Experience

AI/ML Literacy

Masterful Communication

Execution Excellence

Growth Mindset

Technical Leadership

Tools

Jira

Linear

Job description

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 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.

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [e-mail]. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

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