Head of AI Engineering

Be-IT Resourcing Ltd
Manchester, United Kingdom
Today
£85,000 – £110,000 pa

Salary

£85,000 – £110,000 pa

Job Type
Permanent
Work Location
Hybrid
Seniority
Director
Education
Degree
Posted
30 Apr 2026 (Today)

Benefits

Competitive salary Equity
Share
Save job
Create job alert

Head of AI Engineering

Permanent - Manchester

Hybrid with a focused on-site presence

Join a pioneering 5yr+ TechBio company at the intersection of AI, synthetic biology, and industrial biotechnology. You will lead the building of an AI engineering platform connecting computational design, experimental validation, and real-world commercial outcomes. Reporting directly to the CEO, sitting on the management team, and engaging with the Board.

This is a hands-on leadership role with genuine scope to shape the company's long-term technical position.

The tasks of a Head of AI Engineering will include:

  • Build & lead the AI engineering team; hiring, coaching, designing, delivering.
  • Contribute hands-on in coding, architecture, and technical problem-solving.
  • Define and build the AI platform connecting data, models, workflows, and learning loops.
  • Design and deploy agentic AI capabilities that improve scientific workflows and platform intelligence.
  • Build the software foundations for autonomous closed-loop experimentation linking computational design and lab validation.
  • Partner with leadership to translate challenges into scalable AI systems.
  • Shape technical strategy, hiring, and engineering standards as company scales.

To progress as a successful Head of AI Engineering, you will require:

  • 5+ years leading engineering, ML, or AI teams at Director or equivalent level.
  • Deep expertise in AI/ML; model architectures, training, evaluation, and production deployment.
  • Strong software engineering background building production-grade AI platforms and infrastructure.
  • Proven experience building and deploying agentic systems into live workflows.
  • A player-coach approach; equally comfortable writing code, setting architecture, and leading people.
  • Strong communication skills across technical, scientific, and executives.

Highly desirable skills include:

  • Exposure or understanding of AI and ML in a scientific or biotech environment
  • Familiar with specialised datasets, iterative learning loops, or semi-autonomous experimentation systems.

Please Note

  • Own eligibility to work in the UK — sponsorship is not available for this role.
  • Significant experience in elite level AI environments is critical.

Rewards & Benefits

  • Competitive salary plus equity.
  • Senior leadership role with direct CEO and Board exposure.
  • The opportunity to build something unique in a well-backed, science-led environment.

Keyword terminology

AI Engineering, Machine Learning, Agentic AI, AI Platform, Closed-Loop Experimentation, Autonomous Experimentation, Protein Engineering, Biocatalysis, Computational Biology, Synthetic Biology, Deep Tech, TechBio, Director of Engineering, ML Platform, AI Infrastructure, Lab Automation, Bioinformatics, Player-Coach, Engineering Leadership, AI Agents, LLMs, Python, Numpy, MLOps, Life Sciences AI, Biotechnology.

Related Jobs

View all jobs

Head of AI – 120k – 150k GenAI / Agentic AI – Brighton – AI-native Scale-up

Opus Recruitment Solutions Brighton, United Kingdom
£120,000 – £150,000 pa Hybrid

Senior Machine Learning Data Scientist - Credit Risk

Martin Veasey Talent Solutions Northampton, Northamptonshire, United Kingdom
£80,000 – £120,000 pa Hybrid

ML Ops Engineer | York

Oliver James North Humberside, United Kingdom
£50,000 – £70,000 pa Hybrid

Data Engineer

Sanderson Bristol, United Kingdom
£45,000 – £48,000 pa Permanent

AI Engineer

Harnham - Data & Analytics Recruitment Grimsby, DN31 1EW, United Kingdom
£70,000 – £90,000 pa Hybrid

EMEA Energy Industry Go-To-Market (GTM) Leader

Databricks United Kingdom
£100,000 – £150,000 pa Hybrid

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.