Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Head of AI Engineering

BuildPrompt
Greater London
9 months ago
Applications closed

Related Jobs

View all jobs

Associate Director, AI Data Scientist

Head of Machine Learning and AI

Head of Data Science

Principal Machine Learning Engineer

Executive Director / Principal Machine Learning Engineer

Principal Data Scientist

Head of AI Engineering


Location: Hybrid – London-based (Flexible - ±3 days in the London office – 180 Strand, Temple)


Who we are: BuildPrompt is a cutting-edge startup working with some of the most well-known names across the built environment. We're revolutionising how industries interact with their data through advanced machine learning and AI-powered insights. Our clients range from international airports to mega rail projects and global real estate portfolios. We're seeking an exceptional ML engineering leader to drive the technical evolution of our AI platform.


Role Summary: As Head of AI Engineering at BuildPrompt, you'll lead the technical development and optimisation of our AI/ML systems. Your focus will be on enhancing our RAG (Retrieval-Augmented Generation) pipeline, fine-tuning large language models, and building scalable ML solutions that transform complex enterprise data into actionable insights.


Key Responsibilities:

Machine Learning Engineering:

  • Architect and optimise production-grade RAG pipelines
  • Design and implement sophisticated ML systems for information retrieval and generation
  • Lead model selection, fine-tuning, and evaluation processes
  • Develop metrics and monitoring systems for ML model performance
  • Optimise model inference and deployment pipelines


Technical Leadership:

  • Lead a team of ML engineers in developing and deploying AI solutions
  • Design and implement ML infrastructure and data pipelines
  • Establish best practises for ML development, testing, and deployment
  • Guide architectural decisions for AI/ML systems
  • Implement ML ops practises for model monitoring and maintenance


Product Development:

  • Work with product teams to translate business requirements into ML solutions
  • Define technical specifications for new AI features
  • Lead proof-of-concept development for new ML capabilities
  • Optimise model performance for production environments


Research & Innovation:

  • Drive research into cutting-edge ML techniques, particularly in RAG and LLMs
  • Evaluate new ML models and approaches for potential implementation
  • Develop novel solutions for complex information retrieval challenges
  • Create frameworks for systematic model evaluation and improvement


Required Experience & Skills:

  • Masters/PhD in Computer Science, Machine Learning, or related field
  • 5+ years of ML engineering experience, with focus on production systems
  • Deep expertise in building and optimising RAG systems
  • Extensive experience with LLMs and fine-tuning techniques
  • Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow)
  • Experience with vector databases and embedding models
  • Track record of deploying ML systems at scale


Technical Skills:

  • Advanced knowledge of ML ops and model deployment
  • Expertise in information retrieval and natural language processing
  • Experience with distributed systems and cloud computing
  • Proficiency in ML infrastructure and pipeline development
  • Understanding of ML monitoring and evaluation metrics


Package:

  • Competitive salary
  • Share options
  • Flexible working
  • Learning and development budget


Why BuildPrompt? Join us in pushing the boundaries of what's possible with ML in the built environment. You'll work with cutting-edge technology, solve complex technical challenges, and have the opportunity to shape the future of AI applications in enterprise settings. We're backed by leading investors and growing rapidly.


Ready to lead ML innovation? If you're passionate about building sophisticated ML systems and want to work at the forefront of AI technology, we want to hear from you.

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.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.