Vice President of Engineering | Biology & AI

VP of Engineering - Biology & AI

London - Hybrid

About the Company:

My client is a fast-growing biotechnology company at the cutting edge of biological discovery. By combining a proprietary multi-billion-gene dataset with advanced AI and machine learning, they are redefining what is possible in genomics, therapeutics, nutrition, and agriculture.

Having recently announced a pre-series C round of funding, they have scaled their data asset tenfold, creating one of the world’s largest biological datasets. The team comprises biologists, engineers, ML researchers, and field scientists who collaborate across disciplines to uncover previously undiscovered biology and translate it into actionable insights.

The Role:

They’re looking for a VP of Engineering to set and deliver a multi-year engineering strategy across infrastructure, MLOps, and core software platforms. You’ll work closely with the executive team and report into the C-suite, owning how engineering supports large-scale scientific and AI research.

The engineering function sits at the centre of the company’s discovery platform. The team builds and operates systems that handle massive biological datasets, GPU-heavy model training, and production-grade deployment of AI models. This role combines deep technical leadership with people leadership at scale.

From day one, you’ll take ownership of architecture, team structure, and execution. You’ll be responsible for scaling systems and teams as data and compute grow rapidly, while building a strong engineering culture and clear career paths.

Key Responsibilities:

* Lead and scale multiple engineering teams across infrastructure, MLOps, data pipelines, and internal tooling

* Define long-term architecture for hybrid cloud and on-prem compute, including Kubernetes-based orchestration and storage systems

* Own production-grade ML deployment pipelines, including training, validation, versioning, monitoring, and reliability

* Build strong internal developer platforms and self-service tooling

* Partner closely with Research, Data Science, and Product to turn research needs into robust engineering systems

* Establish engineering best practice around security, reliability, and compliance

* Set clear career frameworks, hiring plans, and performance processes

* Own delivery planning, budgeting, and senior technical decision-making

* Manage strategic technical partnerships and vendor relationships

About You:

* 10+ years of engineering experience, with 5+ years in senior leadership roles

* Proven experience scaling teams and systems through rapid data or compute growth

* Strong background in distributed systems, infrastructure, and MLOps

* Experience supporting GPU-heavy training or inference workloads

* Track record of taking research or prototype code into production systems

* Comfortable working at exec level and influencing company-wide technical direction

* Strong people leadership skills with a focus on mentoring and growing leaders

* Clear communicator who works well across technical and non-technical teams

Desirables:

* Exposure to computational biology, genomics, or scientific data workflows

* Hands-on experience with Kubernetes, Airflow, Argo, or similar tooling

* Familiarity with security, compliance, or regulated environments

* Experience working with cloud providers and large-scale GPU infrastructure

What they can offer in return:

* The chance to play a key role in a fast-moving and impactful field

* A supportive and collaborative work environment based in central London, with flexibility and focus on development

* Competitive salary with equity

* Comprehensive benefits including private medical cover, pension, generous time off, and enhanced parental support

* Additional benefits such as childcare support, cycle to work scheme, and income protection

Please apply ASAP for immediate consideration and a fast-moving interview process!

Keywords: VP of Engineering, Vice President of Engineering, Head of Engineering, Engineering Director, Engineering Leadership, Senior Engineering Leader, Biotechnology, BioAI, AI, Artificial Intelligence, Biological Datasets, Foundation Models