Artificial Intelligence Jobs

Faculty · London

Builds client-facing products that visualise insights from data scientists, working in cross-functional delivery teams within the National Security and AI Safety unit. Owns frontend standards and reusable component libraries across the company, sets up deployment infrastructure, and mentors other engineers. Requires React, TypeScript, ES6, HTML/CSS3 and data visualisation such as d3, with cloud exposure to AWS, GCP or Azure.

Faculty · London

Build and scale AI-powered systems for public sector clients, owning the full stack from Python/FastAPI backends to TypeScript and React or Vue frontends. Work in cross-functional teams with data scientists and product managers, deploying to AWS, Azure or GCP with Docker and building data pipelines and cloud infrastructure. May require UK Security Clearance and occasional on-site work with government clients.

Carrington Recruitment Solutions · Sheffield · £80,000 – £90,000 pa

Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards while collaborating with Product, Architecture and wider technical groups. Work spans C#, .NET, Python, Azure PaaS, SharePoint and React, with an AI edge including GenAI tooling and taking experiments through to production-grade solutions.

Carrington Recruitment Solutions · Leeds · £80,000 – £90,000 pa

Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards and shaping delivery. Work spans C#, .NET, Python, Azure PaaS, SharePoint and React, with an AI-native edge using GenAI tooling. Mainly remote with occasional light travel to Leeds and other offices.

Wayve · London

Lead the technical direction for an offline 3D reconstruction system that turns raw vehicle sensor data into quality-assessed 3D ground-truth geometry and ego motion. The role spans SLAM, lidar point-cloud registration, state estimation and sensor fusion, with responsibility for architecture, roadmaps, prototypes and cross-functional alignment across perception, calibration and validation teams.

Anthropic · London · £165,000 – £190,000 pa

Pre-sales architect acting as a trusted technical advisor to large enterprises, helping them integrate and deploy Claude across their technology stack. Combines deep LLM expertise with customer-facing work, from technical discovery and evals to scalable architecture design, while feeding integration insights back to Product and Engineering.

The Portfolio Group · Manchester

Set the AI vision and roadmap while staying hands-on, architecting and deploying machine learning and generative AI solutions into production. Work spans RAG, LLMs, vector search and knowledge graphs, plus building a cross-functional team and establishing AI governance. Based fully on-site in Manchester, reporting into senior leadership.

Thought Machine · Lisbon, Portugal

Full-stack role building end-to-end features across web applications and backend services, with React and TypeScript on the front end and REST APIs behind. Engineers own requirements from design and task breakdown through testing, debugging and production, working in a cross-functional team for banking clients.

Thought Machine · Lisbon, Portugal

Owns complex, ambiguous technical challenges end-to-end, shaping long-term platform architecture and company-wide engineering standards. Drives adoption of AI tooling, leads technical interviews, and mentors senior engineers while acting as a link between leadership and engineering teams. Based in the Lisbon office, requiring three days a week onsite.

Palo Alto Networks · London

Acts as "customer zero" and advocate for Identity Security, defining and validating enterprise architectures for machine identity, secrets governance and agentic identity management. Produces technical content such as blogs, whitepapers and deep-dive decks, builds reference architectures and demos, and partners with specialist sellers and solutions teams on complex customer engagements. Also feeds product insights and leads market education through executive briefings and conference talks.

PhysicsX · Singapore

Join a new Singapore research team building physical foundation models for industrial engineering, translating physics challenges into mathematical formulations and training deep learning models on large datasets. You will own research workstreams, run experiments, and communicate results to customers and at publication venues, with a focus on operator learning, geometric deep learning, or generative models for geometry and spatiotemporal data.

Databricks · London

Lead and scale the UK Forward Deployed AI Engineering team, delivering professional services engagements that help EMEA customers productionise GenAI and ML applications. The role combines people leadership, executive customer relationships, and cross-functional work with Product, Research and Sales to shape delivery models and the product roadmap.

PhysicsX · New York, United States · US$150,000 – US$250,000 pa

Customer-facing role owning the full customer journey, from onboarding and change management to roadmap planning and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate engineering and physics challenges into product opportunities, tracking engagement and measuring value. Based in Manhattan with hybrid remote flexibility.

Wayve · London

Lead a team of ML engineers and applied scientists building synthetic data from generative world models like GAIA-3, turning them into a production engine for training-grade driving experience. Own the loop end to end, from checkpoint and large-scale GPU inference to artefacts landing in driving-model training, while setting technical direction on rig transfer, pose transfer and controllability.

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

This role involves leading research in privacy-preserving generative AI, focusing on techniques like differential privacy, federated learning, and secure inference. The scientist will design and validate machine learning models, translate research into deployable systems, and contribute to publications and collaborations within a multi-partner environment. Emphasis is placed on responsible AI, reproducibility, and mentoring junior team members.