Artificial Intelligence Jobs

CrowdStrike · Reading · £140,000 – £215,000 pa

Lead a growing team of engineers building self-service infrastructure-as-code primitives, high-availability platforms and cloud cost optimisation across a multi-cloud environment. The role combines people management, on-call ownership and hands-on architecture of large-scale distributed systems, with hybrid working near Reading.

CrowdStrike · Boston, United States · US$140,000 – US$215,000 pa

Lead a team building self-service infrastructure-as-code primitives, high-availability services and cloud cost optimization across a multi-cloud environment. The role combines people management with hands-on architecture of large-scale distributed systems, using tools like Terraform, Pulumi, Chef and Python or Go, with a strong SRE and GitOps focus.

OpenAI · London

Lead a team of senior Applied AI Architects acting as the technical "CTO of the book of business" for OpenAI's largest enterprise customers across North EMEA. Own technical account strategy, resource allocation and paths to production across ChatGPT Enterprise, the API, Codex and agentic solutions, while coaching the team and serving as an executive technical sponsor.

Noir · Abingdon · US$170,000 – US$195,000 pa

Take full ownership of the technology function at an early-stage AI venture, making key architectural decisions and building a founding engineering team. The platform combines proprietary data, real-time insights and advanced AI (LLMs, RAG, AI agents) for a specialised luxury and wealth intelligence market. The role blends hands-on engineering with founder-level strategy and equity.

Noir · London · £160,000 – £180,000 pa

Take full ownership of the technology function at an early-stage AI venture, making key architectural decisions and building a founding engineering team. The platform combines proprietary data, real-time insights and advanced AI, with work spanning LLMs, RAG pipelines, AI agents, data infrastructure and cloud architecture. It is a hands-on founder role rather than a traditional management position.

eFinancialCareers · London

Leads the design, development and operation of high-rigor analytical and machine-learning systems across a complex, regulated financial-services estate, defining the AI/ML roadmap while remaining hands-on. Owns the full model lifecycle from feature engineering and back-testing to deployment, monitoring and incident response, with models expected to be explainable and production-grade. Works closely with engineering, data platform and product teams, mentoring other data scientists with limited line management.

Anthropic · London · £190,000 – £230,000 pa

Lead and grow a distributed EMEA team of Applied AI Architects, setting pre-sales standards and acting as technical lead on strategic digital-native accounts. The role involves use case scoping, POCs, demos, and guiding customers through GDPR, EU AI Act, and data residency requirements while partnering with Sales, Product, and Engineering.

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

Builds and operates large-scale CI infrastructure supporting thousands of daily builds across multiple cloud providers, including intelligent test selection, merge queue management, and flake detection. Works within the Developer Productivity org to improve reliability and developer velocity across a monorepo.

Wayve · London

Lead the Applied Methods Data Science team, partnering with the Autonomy organisation to turn experimental and observational analysis of real and simulated driving into evaluations and insights. Set three-, six- and 12-month roadmaps, review technical proposals for statistical rigour, hire and grow data scientists, and build tooling to scale the team's capability.

Amazon · London

Owns the commercial vision and go-to-market strategy for AWS AI services across UK Central Government and Transport, leading complex multi-stakeholder sales engagements from opportunity identification to close. Works with senior government and transport leaders on use cases like citizen services, border management and infrastructure planning, navigating public sector procurement frameworks such as G-Cloud and GCA.

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.

Maxwell Bond · Gateshead · £85,000 – £95,000 pa

Hands-on technical leadership role owning AI development for a product-led platform, taking LLM-powered features from concept to production. Involves architectural decisions on LLM integration, retrieval systems, model selection, plus AI evaluation, monitoring, security and cost management, while mentoring engineers. No direct reports initially.

Data Idols · London · £105,000 – £120,000 pa

Hands-on technical leadership role driving the design, development and deployment of AI, Machine Learning and Generative AI solutions, including LLMs and agentic AI. Partners with business and technology stakeholders to identify high-value use cases, prototype rapidly and take solutions through to production, while shaping the AI technical roadmap and engineering best practices.

Morson Edge · West Yorkshire · £170,000 – £180,000 pa

A senior leadership role owning the data and AI strategy, roadmap and technical direction across the organisation. Day to day it spans hands-on work with generative AI, LLMs, RAG and agentic architectures, MLOps and data platform governance, plus building and leading a high-performing Data & AI team and partnering with Product, Engineering, Architecture and Security to scale prototypes into production.

Key Recruitment · Southampton · £70,000 – £92,258 pa

Lead the creation of an enterprise-wide AI Accelerator programme, combining technical leadership with programme-level influence. You will prototype with geo foundation models, agentic systems and LLM orchestration, write production-grade code, mentor participants and engage senior stakeholders to embed responsible AI across a geospatial data business.