Artificial Intelligence Jobs

Wayve · London

Develops, tunes and validates trajectory-generation and motion control algorithms that translate the AI Driver's outputs into safe, smooth vehicle motion across ADAS and AV platforms. Writes latency-sensitive, production-quality C++ control software, using simulation, closed-loop evaluation and on-road testing to characterise controller behaviour and support new vehicle platforms.

Wayve · London

You'll design, build and operate shared infrastructure for model access, agent runtimes and observability, taking projects from problem definition through technical design, deployment and ongoing operation. Working with security, IT and engineering teams, you'll create governed access layers, reusable tooling and standards so teams can run AI agents in production without one-off infrastructure.

Harnham - Data and Analytics Recruitment · London · £80,000 pa

Builds internal AI agents, tools and prototypes within a small central technical team, turning complex group data into usable products at speed. Work spans Python, TypeScript and SQL, modernising legacy systems, wrapping systems in scalable APIs and contributing to shared data and entity platforms, with weekly demonstrable output.

Adecco · Cambridge

Lead the AI engineering strategy and delivery of advanced AI products and platforms, reporting to executive leadership. Manage software, platform and AI engineering teams, driving adoption of Agentic AI, LLMs, RAG and multi-agent architectures on Azure, AWS or GCP. Requires a strong engineering background and proven leadership in high-growth environments.

Adecco · Cambridge

Lead the AI engineering strategy and delivery of advanced AI products and platforms, reporting to executive leadership. Manage software, platform and AI engineering teams, driving adoption of Agentic AI, LLMs, RAG and multi-agent architectures across Azure, AWS or GCP. Requires a strong engineering background and proven leadership in high-growth environments.

Databricks · London

Customer-facing role building and productionising data and AI solutions on the Databricks platform, owning architecture and design decisions for end-to-end systems spanning data engineering, ML/AI and application development. Embeds with client teams from engineers to executives, delivering production-grade reference architectures and reusable accelerators, with around 20% travel.

Faculty · London

Lead the technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging research and production impact. The role involves capability testing for Frontier AI models, multi-agent systems, scalable cloud infrastructure and safety-first frameworks, while advising senior clients and mentoring engineering talent.

MFK Recruitment · Brentford · £70,000 – £95,000 pa

Design and deploy production-grade computer vision systems using deep learning techniques such as CNNs and Vision Transformers, translating research into robust AI solutions for defence and security applications. Work across the full development lifecycle, from model design and training to deployment on cloud and edge platforms. Collaborate with researchers, engineers, and customers in a technically challenging environment focused on real-world autonomy and perception systems.

Aioi Nissay Dowa Europe · United Kingdom · £81,322 – £112,488 pa

Dual role combining line management of a growing ML engineering team with hands-on technical delivery across multiple client projects. You'll shape ML engineering practice, lead multidisciplinary teams, oversee solution design and quality assurance, and support pre-sales and use case discovery alongside commercial teams.

Luminance · Cambridge

Join a small, dynamic R&D team prototyping and implementing new approaches to AI problems, evaluating output quality, efficiency and feasibility against other techniques in a data-driven way. Work spans data science on large datasets, modelling and evaluation, using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn. Open to graduates as well as senior candidates with published work in NLP, Computer Vision or Deep Learning.

Deerfoot Recruitment Solutions · Didcot · £700 – £900 pd

Architect and build multi-agent AI systems end-to-end, combining frameworks like LangGraph or Haystack with bespoke orchestration, state management and tool-calling logic. Embed LLMs and vision-language models into live reasoning, search and task-execution workflows, deploying across cloud and on-premises environments with monitoring, evaluation and guardrail tooling. Set technical standards for agentic AI within the team, working with a biotech and pharma customer.

Thought Machine · Lisbon, Portugal

Builds end-to-end features across web applications and backend services, owning requirements from engineering design through task breakdown, implementation and production debugging. Works with React, TypeScript and REST APIs in a cross-functional team of backend, front-end and full-stack engineers, with automated testing integrated throughout the development lifecycle.

Faculty · London

Lead the design, build and deployment of production-grade ML systems for national security and AI safety clients, including capability testing of frontier models. Act as a technical advisor to customers, define best practices for deploying ML at scale, and mentor junior engineers. Distinct for its focus on red teaming, evaluation and high-stakes government and frontier lab work.

Hays Technology · London · £100,000 – £110,000 pa

Hands-on role building the backend services, APIs and data pipelines behind a new AI layer for an investment management firm's portfolio platform. Involves LLM applications such as agent workflows, tool use and RAG, plus security controls, automated tests, AI evaluations and monitoring of accuracy, latency and cost in production.

WeDoTech · London · £120,000 – £160,000 pa

Hands-on technical leadership role building and scaling enterprise Generative AI, LLM and agentic AI systems across multiple engineering teams. Involves designing production-grade RAG and multi-agent solutions, shaping reusable AI frameworks and standards, and ensuring reliability and governance in a regulated financial services environment.