Vice President, Build — Data, Engineering & AI in Surrey

Vice President, Build — Data, Engineering & AI in Surrey

Surrey Full-Time 72000 - 88000 £ / year (est.) No working from home possible
Pfizer, S.A. de C.V

At a Glance

  • Tasks: Lead data and AI initiatives, ensuring seamless integration and delivery across teams.
  • Company: Join a forward-thinking tech company focused on innovation and collaboration.
  • Benefits: Attractive salary, comprehensive health benefits, flexible work options, and growth opportunities.
  • Other info: Dynamic role with a focus on empowering teams and driving impactful projects.
  • Why this job: Shape the future of AI and data management while working with top talent.
  • Qualifications: Legal degree in a technical field and proven leadership experience required.

The predicted salary is between 72000 - 88000 £ per year.

Vice President, Build — Data, Engineering run the Collibra dictionary, master Systems Integration partners and contractors crew in—never as standing outside teams.

Engineering talent is never fragmented, and capacity decisions are transparent against the agreed portfolio priority queue.

Own product and delivery management: roadmap and translation on the way in; scrum and programme delivery on the way through.

Build the agent library and standards; deliver the reusable data agents of the AICL and their agent‑facing data contracts.

Run AI evaluation and assurance independently of the builders: evals, red‑team, model‑tier proof and the clearance evidence pack.

Own Agent Ops and technical run: agents and classic ML in production, AI cost operations, and solution run land the commercial data foundation as a certified source on Loom, including the Collibra‑to‑Loom reconciliation.

Keep what is live running well: program support, maintenance, upgrades and data quality across the estate.

Keep AI running costs visible and managed, feeding the cost signal back to Strategy, Value peer for Strategy, Value pods owned by Pillar 1 product owners and crewed from this pillar.

Pillar 3 — hand‑offs into adoption, localisation and the in‑market network for everything shipped.

Global Commercial Analytics — data scientists, engineers and project managers crewing into pods via the operating agreement.

Legal evaluation independent of the builders; production quality as a habit.

Equity — one deployable pool serving all markets and functions, not the best‑connected ones.

Joy — engineers doing their best work in small, empowered pods, with agents drafting first‑pass code and people reviewing, hardening and owning.

Decides technical architecture and standards from raw data to running agent, within the CIO platform guardrails.

Owns delivery capacity allocation and crewing recommendations against the agreed portfolio priority queue, with escalation where demand exceeds capacity or technical risk changes sequencing.

Owns the ship/no‑ship evidence pack through independent evaluation; Legal degree in a technical discipline required, advanced degree preferred.

Proven ability to operate as a senior enterprise leader in a complex global matrix, influencing senior business, technology, legal/compliance, medical, finance, PX and market stakeholders without relying solely on direct authority.

Technical skills

Vice President, Build — Data, Engineering & AI in Surrey employer: Pfizer, S.A. de C.V

Pfizer is an exceptional employer that prioritises employee well-being and professional growth, offering a hybrid work model that fosters flexibility while ensuring collaboration. With competitive compensation packages, including performance bonuses and comprehensive health benefits, employees are supported in both their personal and professional lives. The vibrant work culture encourages innovation and engagement, making it an ideal place for those looking to make a meaningful impact in the healthcare sector.

Pfizer, S.A. de C.V

Contact Details:

Pfizer, S.A. de C.V Recruitment Team

We think you need these skills to ace Vice President, Build — Data, Engineering & AI in Surrey

Data Management
Systems Integration
Product Management
Scrum
Programme Delivery
AI Evaluation
Machine Learning Operations