Technical Programme Manager, Product (London, UK)

Hive Science is a tech start-up whose technologies are in use by many of the world’s largest brands including Ford, Edward Jones & Kroger. The Hive platform is delivering novel intelligence at the intersection of quantitative social psychology, behavioral science & AI/ML to accelerate & transform how work is done. We’re looking for someone to join our team and get on board this rocket ship with us.

About the role:

This is a critical hire for Hive Science. As we grow our engineering, data science, and AI teams, we need a Technical Programme Manager who can bring structure, rigour, and momentum to how we plan, execute, and ship. This role is the connective tissue of the entire product and technology organisation — the person who ensures that our multi-disciplined teams across social science, data science and engineering are all pulling in the same direction, at the right pace, with the right priorities.

You will own the delivery process end-to-end: sprint planning, daily stand-ups, backlog management, definition of ready and done, code review governance, technical debt tracking, and release coordination. You will work across all workstreams simultaneously — core platform and ecosystem pipelines, new GPT and agentic AI product builds, MLOps, infrastructure, and data science model development — and ensure every workstream is moving efficiently and transparently.

This is not a project coordination role. We need someone with a strong enough technical understanding to challenge estimates, spot risks early, ask the right questions in a stand-up, and understand why a task is blocked. You don't need to be an SME in every discipline — but you need to understand enough about full stack engineering, DevOps, MLOps, and AI / data science to manage the work credibly and earn the respect of the team.

What You'll Be Doing:

As Technical Programme Manager, you will be the operational heartbeat of Hive product. You will ensure the organisation runs with clarity and focus — that the right work is being done, in the right order, by the right people, and that nothing important falls through the cracks.

You will constantly be across multiple concurrent workstreams spanning platform engineering, AI/ML model development, product build, and infrastructure. We can't define everything you will be doing because the product landscape moves fast — you need to be the kind of person who thrives in ambiguity, adapts quickly, and brings calm and structure wherever you go.

Key areas of responsibility include:

Delivery Management & Sprint Execution:

• Own and run the daily stand-up across our product team — keeping them tight, purposeful, and focused on blockers and progress rather than status theatre.

• Lead sprint planning sessions: working with the SMEs to define, size, and sequence work into well-structured, achievable sprints.

• Maintain and manage the backlog across all workstreams — ensuring cards are well-defined, correctly prioritised, and always ready to be picked up.

• Track sprint velocity, identify delivery risks early, and proactively escalate or re-plan when commitments are at risk.

• Own the sprint retrospective process — driving continuous improvement in how the team works, not just what they build.

Cross-Team Coordination & Dependency Management:

• Coordinate delivery across all disciplines identifying cross-team dependencies and ensuring they are surfaced and resolved early.

• Manage the handoff between social science direction, data science model development and engineering productionisation — ensuring the work we do from research to production has clear acceptance criteria, deployment plans, and sign-off processes.

• Coordinate delivery across new product workstreams and core platform/pipeline work — ensuring neither track blocks the other and that shared infrastructure decisions are made collaboratively.

Estimation, Roadmap Planning & Capacity Management:

• Work closely with the SMEs to build reliable delivery estimates for new product features, infrastructure work, and AI/ML model development.

• Maintain a rolling view of team capacity — accounting for planned leave, context-switching costs, and the reality of working in a fast-paced startup environment.

• Support the Leadership team in translating the product and technology roadmaps into sprint-level delivery plans with realistic timelines.

• Challenge and interrogate estimates constructively — asking the right questions to surface hidden complexity, unclear requirements, or unrealistic assumptions before they become delivery problems.

• Track actuals against estimates over time to improve planning accuracy and build a clearer model of team velocity across different types of work.

Tooling, Process & Documentation:

• Own Hive's delivery tooling — with a preference for Notion as the primary workspace for sprint boards, backlog management, documentation, and delivery tracking.

• Establish and maintain clear, consistent process documentation: how sprints work, how cards are written, how work is reviewed and signed off, and how releases are managed.

• Ensure the team is working from a single source of truth — that the state of every workstream is visible, up to date, and accessible to anyone who needs it.

Stakeholder Communication & Reporting:

• Provide the leadership team with regular, clear delivery updates — translating complex multi-workstream progress into concise, accurate summaries.

• Flag risks, blockers, and scope changes proactively — with a proposed solution wherever possible, not just a problem statement.

Required Skills & Experience:

Technical Programme Management:

• Proven experience as a Technical Programme Manager, Senior Scrum Master, or Delivery Lead in a software product or technology company — ideally in an early-stage or high-growth startup environment.

• Strong track record of managing delivery across multiple concurrent technical workstreams simultaneously, including engineering, infrastructure, and data/ML workstreams.

• Deep fluency in agile delivery methodologies — Scrum, Kanban, or hybrid approaches — with strong opinions about what works and what doesn't in a fast-paced environment.

• Experience owning and enforcing Definition of Ready, Definition of Done, sprint planning, retrospectives, and backlog grooming at an organisational level.

• Demonstrable experience managing technical debt as a first-class delivery concern, not an afterthought.

Technical Understanding:

• Strong enough technical understanding of full stack engineering (frontend, backend APIs, cloud infrastructure) to manage estimates, challenge scope, and understand blockers without needing line-by-line explanation.

• Familiarity with DevOps and infrastructure concepts — CI/CD pipelines, IaC, containerisation, cloud environments — sufficient to understand the work being done and the risks involved.

• Working knowledge of MLOps and AI/ML model development lifecycles — understanding how models move from research and prototyping through to production deployment, and what the handoff process involves.

• Familiarity with LLM/GPT product development — understanding the nature of building AI-powered features, agentic workflows, and generative product experiences, including the unique delivery challenges they present (probabilistic outputs, evaluation complexity, governance requirements).

• Comfort engaging with technical conversations at a conceptual level — not needing to write code, but needing to understand what engineers and scientists mean when they describe their work.

Delivery Tools & Practices:

• Strong experience with project and delivery management tooling — Notion experience is a preference; the ideal candidate has used it and is comfortable building and maintaining delivery workflows within it.

• Experience with engineering workflow tools such as GitHub, Linear, Jira, or equivalent — understanding how development tickets, PRs, and code review processes are managed.

• Ability to design clear, practical delivery processes that a technical team will actually follow — not over-engineered bureaucracy, but the right amount of structure for a high-performing startup team.

Overall Work Experience & Additional Details:

You may have come from a product engineering team at a scale-up, a delivery lead role at a technology consultancy, or from a startup where you owned the entire delivery function yourself. You understand what good engineering delivery looks like — not just the process, but the culture — and you know how to bring that out in a team without slowing them down.

As a fast-paced startup, each day is different from the one before. We're nimble and creative, and value intellectual humility. We work really hard because we're all 100% dedicated to the future we're building. Our work is stimulating, challenging, and exciting. And our team is awesome. At Hive we only hire exceptional people, so you'll be in good company — surrounded by passionate, insanely smart people who want to build the future of customer intelligence.

Specifically we're looking for someone who will thrive in this type of environment:

• Fast-paced startup with competing demands and multiple priorities ongoing

• A natural organiser who brings clarity and calm to complexity

• A 'solve the problem' mentality — focused on unblocking progress, not documenting obstacles

• Scrappy and creative, but also structured and reliable when the team needs a steady hand

• Strong passion for the Hive Science mission and a love of the scientific method

• Genuinely excited by the intersection of psychology, behavioural science, and cutting-edge AI — curious enough to understand what the team is building and why it matters

This is an in-person role in London, UK - we cannot consider candidates who do not currently live within commuting distance.