Artificial Intelligence Jobs

Thought Machine · London

Technical Programme Managers own the delivery of complex, multi-team engineering programmes, from planning and milestones through to coordination and stakeholder communication. The role requires hands-on understanding of microservice stacks such as Kubernetes, Kafka and AWS/GCP, and involves driving continuous improvement across a fast-paced engineering organisation.

EMBS Engineering · London · £60,000 – £75,000 pa

Hands-on engineering role building core services and features for an enterprise-grade Generative and Agentic AI platform for a financial services client. Involves Python/FastAPI backend development, LLM integration, RAG architectures, prompt orchestration and AWS services such as Bedrock, AgentCore and EKS, plus CI/CD and DevOps. Works alongside AI engineers, architects and platform specialists on secure, production-ready AI applications.

Synextra · Warrington · £65,000 – £80,000 pa

Senior escalation point for complex Azure incidents across customer environments, spanning compute, networking, DNS, identity and storage, while also contributing to development sprints. Builds and maintains Azure infrastructure with Terraform, improves CI/CD pipelines in Azure DevOps and GitHub Actions, and supports the Azure environments behind the company's AI products. Includes an on-call rota and mentoring of other engineers.

Carrington Recruitment Solutions · London · £95,000 – £105,000 pa

Hands-on lead role guiding a small development team across a portfolio of applications in a highly regulated professional services environment. Involves C#, .NET, Python and Azure PaaS work, with a strong AI focus spanning GenAI tools, Co-Pilot Studio and taking experiments through to production-grade solutions, while shaping delivery and engineering standards alongside Product and Architecture.

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.

Wayve · London

Set the technical direction for a petabyte-scale storage platform underpinning autonomous driving data, leading a multi-quarter programme from architecture to adoption. Build production services and controllers in Python or Go with Kubernetes and Terraform, optimising read performance, caching and cost while partnering with ML, data, security and privacy teams.

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.

Anthropic · London · £325,000 – £390,000 pa

Lead and scope multi-month infrastructure projects, making architectural decisions for large-scale distributed systems that train and serve AI models. Work spans Kubernetes clusters, data pipelines, databases and observability tooling, partnering with research and product teams while mentoring engineers and shaping incident response and on-call practices.

PhysicsX · San Francisco, United States · US$150,000 – US$190,000 pa

Builds and deploys machine learning pipelines for industrial physics applications, working directly with customers on-site to embed AI models into practical tools. Involves manipulating 3D point-cloud and mesh data, cloud and HPC infrastructure, and translating R&D outputs into reusable libraries and products.

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.

CrowdStrike · London

Builds and maintains a high-performance, fault-tolerant production backbone network spanning multiple cloud providers, covering IP and optical technologies that connect data centres and edge sites. Owns improvement initiatives from funding and planning through implementation, drives capacity forecasting, and participates in a 24x7 on-call rotation.

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.

Experis · London · £600 – £644 pd

Builds production-grade GenAI and Agentic AI products within a product squad, using LLMs, RAG and agentic workflows. Requires strong Python engineering plus LangGraph, vector search, evaluation and Azure AI services to deliver secure, maintainable AI applications.

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.

AI Security Institute · London

Senior individual contributor building and owning shared platform, tooling and infrastructure for a research team, including LLM-based agent systems, evaluation frameworks and supporting infrastructure. Works closely with interdisciplinary researchers to translate varied needs into maintainable Python systems, with strong engineering discipline around testing, documentation and observability. Also contributes to architectural decisions, engineering standards and mentoring through code review and knowledge sharing.