Technical Program Manager, Research to Production, Agent Systems

On-site in London·Added 12 days ago (last checked 1 Oct)

Google

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Requirements

Minimum qualifications:

Bachelor's degree in a technical field, or equivalent practical experience.
5 years of experience in technical program management.
5 years of experience across all phases of a product development from prototype to mass production to end of life.
5 years of experience in software development life-cycle and stakeholder management.
2 years of experience developing or launching products or technologies within GenAI, AI/ML, LLM's.

Preferred qualifications:

Bachelor's degree in Computer Science, AI-related technical field, or equivalent practical experience.
5 years of experience managing cross-functional or cross-team projects.
2 years of experience in software development or engineering.

The role

A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

This role is on the DeepMind team that takes new agent technology from research into production. We are the team responsible for the production agent harness that powers agent experiences across Google, our customers include flagship products such as Search, Workspace and Gemini Spark.

In this role, you will own the path from research into production for agent capabilities, and work with the research engineers focused on improving the harness quality, to better align it with our customer needs via systematic benchmarking and hillclimbing on metrics that our customers care about. You will be responsible for driving the work that improves the quality of the fundamental technology that our product teams depend on.

Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Responsibilities

Own the path from research prototype to production for agent capabilities, from first engagement with the research team through to adoption in a product.
Partner with researchers, research engineers, technical and program leads to understand what they are building and translate this into a prioritized backlog with clear owners, deliverables and timelines.
Set the goals for the agent harness quality improvement workstream, then run its day to day execution, triage, stand-ups, status and escalation. Drive improvement through benchmarking and hillclimbing on metrics customers care about.
Drive production readiness for each effort, load testing, capacity planning, quota, and the right deployment and sandbox environment with the serving team and manage handover into the receiving product team.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

Apply online
Assessments
Online test · Not every role
You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.
Recruiter conversations
With a recruiter · Phone call · 1–2 sessions
One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
Interviews
With a rotating cast of Googlers
A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.
Decision and offer · With a recruiter

Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
AI tools are not permitted during interviews.
For some roles, pre-selected interviews happen virtually before final interviews onsite.