Artificial Intelligence Jobs

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.

eFinancialCareers · Belfast

Hands-on engineering lead building AI-powered products and enterprise-scale applications, staying close to code through architecture, system design and code reviews. Sets technical direction across full-stack ecosystems (frontend, backend, APIs, cloud) using Python, Go, TypeScript, JavaScript or React, Kubernetes and microservices, while mentoring engineers and driving GenAI adoption.

Humanoid · London

Hands-on engineering lead owning the path from AI agent task to healthy deployed change, building secure reproducible agent runtimes, verification tooling, and developer interfaces. Recruits and leads a new developer productivity team while working across Developer Tools, Security, Simulation, and robot software to cut cost and review time per accepted change.

Databricks · London

Lead a delivery team of 8+ engineers building and productionising data and AI solutions on the Databricks platform for enterprise customers. The role blends hands-on technical oversight of Spark, Python/Scala, cloud and MLOps architectures with professional services delivery metrics, hiring and coaching. Hybrid working in London, with accountability for bookings, revenue, margin and customer satisfaction.

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.

Wayve · London

Hands-on role optimising inference for edge accelerators and GPUs so large transformer models run efficiently on low-cost, low-power in-vehicle compute. You'll profile model graphs, compiler/runtime behaviour and kernel execution, implement optimisations like fusion, scheduling and custom kernels, and build benchmarking and regression tests across NVIDIA Orin/Thor and Qualcomm targets, working closely with model, platform and deployment teams.

Wayve · London

Lead large-scale data enrichment and curation for the Core Model Safety team, mining hard and rare events and building workflows across pre/mid-training, reward modelling and self-supervised labelling. Design and train out-of-distribution detection mechanisms for robust driverless operation, working at the intersection of model engineering, infrastructure, compute and data.

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.

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.