Artificial Intelligence Jobs

Wayve · London

Owns shared onboard runtime foundations for autonomous vehicles: application frameworks, communication middleware, lifecycle management, health monitoring and observability. Day to day involves C++ development, end-to-end latency and performance profiling across OS scheduling, memory hierarchy and thread synchronisation, plus porting the stack to new operating systems and compute platforms.

Wayve · London

Lead a London-based team building the on-vehicle experiment platform that lets researchers deploy driving models to vehicles, run experiments and collect training data. You own people, roadmap and delivery, plus partner and OEM relationships, while staying close to embedded Linux systems code in C++ or Python.

PhysicsX · Singapore

Builds physical foundation models for industrial engineering, scaling training across multi-GPU cloud compute and turning research prototypes into robust, optimised implementations. Works closely with research scientists, simulation engineers and customers, owning research work-streams and translating results into reusable libraries, tooling and products.

PhysicsX · New York, United States · US$200,000 – US$250,000 pa

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture design, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter to embed AI models on-site.

OpenAI · London

You'll partner with early-stage startups to embed Codex into their software workflows, building integrations, automations and reusable tools while troubleshooting technical blockers. A large part of the role is outward-facing: leading technical talks, live demos, workshops and hackathons, then feeding developer insights back to OpenAI's product and research teams.

Hyre Ai · London · £50,000 – £60,000 pa

Design and evolve production multi-agent systems using Anthropic, OpenAI and Perplexity models on AWS, extending the company's MCP server with new tools. Build the eval and observability layer with golden datasets, regression suites and LLM-as-judge, own AWS infrastructure (ECS Fargate, Lambda, Step Functions, Bedrock) and guard against prompt injection and PII leakage. Set technical direction and mentor engineers.

CBSbutler Holdings Limited trading as CBSbutler · Uxbridge · £600 – £625 pd

Hands-on technical leadership across a major airline's Data & AI team, driving a 2026 data engineering workstream. You will design scalable AWS data pipelines, implement CI/CD and DevOps practices, and mentor data and software engineers. Snowflake and AI-assisted development experience are desirable.

Tech Recruitment Specialists Ltd · London · £38,000 – £45,000 pa

Supports the development, optimisation and deployment of AI and machine learning models, working with large datasets for preprocessing and training, and helping monitor AI applications in production. Collaborates with software engineers, product teams and data specialists, contributes to backend development and API integrations, and researches new AI frameworks. Emphasis on responsible, ethical AI with bias mitigation, transparency and fairness.

Circle Recruitment · Cardiff · £45,000 – £53,000 pa

Lead the design, development and deployment of AI-powered tools, including automation, RAG and LLM-based workflows, while guiding technical direction and mentoring a small team of engineers. Work with senior stakeholders on secure, scalable, governance-compliant AI systems, using Python, Java or JavaScript/TypeScript with frameworks such as PyTorch and TensorFlow.

Harnham - Data and Analytics Recruitment · Abingdon · US$200,000 – US$225,000 pa

Build scalable data platforms, pipelines and ML infrastructure, and deploy production AI solutions including LLMs, RAG systems and AI agents. Work in a small, highly visible team partnering with investment and operational stakeholders, owning projects end-to-end from design through production and driving architecture decisions.

Harnham - Data and Analytics Recruitment · London · £80,000 – £85,000 pa

Design, build and deploy scalable AI and machine learning solutions from concept to production, including Generative AI applications using LLMs and orchestration frameworks. Write production-grade Python, apply MLOps practices such as CI/CD, containerisation and monitoring, and build data pipelines for training, fine-tuning and inference. Work hybrid in London alongside data scientists, engineers and business stakeholders on large-scale datasets.

Maxwell Bond · London · £150,000 – £175,000 pa

Hands-on role building LLM agent and retrieval systems on a small UK core team, reporting to the Head of Engineering. Work spans LangGraph/LangChain workflows, RAG pipelines with Qdrant and GraphRAG on Neo4j, model integration across Anthropic, OpenAI and Bedrock, plus evaluation harnesses and observability. Token cost, latency and auditability are treated as engineering constraints throughout.

Relation Therapeutics · London

Join the Platform Team to design and scale Kubernetes-based hybrid compute clusters across private and public clouds, building core platform services and APIs. You will own CI/CD pipelines, monitoring, backup and disaster recovery, and work closely with Machine Learning and Data Science teams to support their computational needs.

Anthropic · London · £225,000 – £255,000 pa

Embed directly with strategic enterprise customers to ship production AI applications built on Claude models, delivering artifacts like MCP servers, sub-agents and agent skills. Combines hands-on Python engineering with customer-facing discovery, codifying repeatable deployment patterns and feeding insights back to Product and Engineering. Founding FDE role with frequent travel (25-50%) to customer sites.

Databricks · London

Customer-facing, billable engineering role owning architecture and design decisions while building production-grade data and AI systems on the Databricks platform. Involves embedding with client teams, integrating with their systems, and delivering end-to-end pipelines, ML/AI models and user-facing applications, with around 20% travel to customer sites.