Artificial Intelligence Jobs

• London
• Hybrid
• Senior

Customer-facing engineering role building and productionising data and AI solutions on the Databricks platform. You own architecture and design decisions, delivering end-to-end systems across data engineering, ML/AI and application development, embedding with client teams and travelling to customers around 20% of the time.

Databricks · AWS · Azure +7

• London

Customer-facing AI engineering role delivering professional services engagements, helping clients build and productionize GenAI applications such as RAG, multi-agent systems and Text2SQL. Involves production rollouts, serving as a trusted technical advisor, and collaborating with product and engineering to shape the roadmap.

Databricks · Apache Spark · HuggingFace +7

• London
• Hybrid
• £190,000 – £230,000 pa
• Director · manages people

Lead a team of Technical Deployment Leads embedded with strategic enterprise customers across EMEA, owning portfolio health, delivery strategy and executive relationships. Player-coach role: hire and manage TDLs, run engagement quality reviews, and personally lead the most complex deployments from SOW through production. Partners with Sales, Legal and Product to scale AI delivery playbooks.

Claude

• London
• Hybrid
• £165,000 – £190,000 pa
• Senior

Technical partner to startup founders and engineers building on the Claude Developer Platform, guiding them from technical discovery through deployment. Combines hands-on LLM architecture, evaluation frameworks and Python work with winning technical evaluations alongside Account Executives.

Claude · Claude Developer Platform

• Spain
• Remote
• Senior
• Permanent

Lead and architect research strategy applying LLMs, deep learning and other modern AI techniques to cybersecurity, driving novel approaches to reasoning, summarisation and interactivity. Build production-ready AI systems at massive scale, make strategic decisions on model architectures and deployment, and mentor scientists while shaping the company's AI vision.

CrowdStrike · LLM · Deep Learning Frameworks +2

• Ireland
• Remote
• Senior

Lead applied research applying LLMs, deep learning and other modern AI techniques to cybersecurity, architecting research strategy and making decisions on model architectures, training and deployment. Build production AI systems at massive scale while mentoring scientists and aligning technical strategy with senior leadership. Distinct for its greenfield, research-to-production focus and thought-leadership expectations.

LLM · Deep Learning Frameworks · GPU +1

• London
• Mid-level

Day-to-day responsibility for requesting data, monitoring and enhancing Financial Crime Key Risk Indicators and management information. Builds and maintains MI dashboards, automated data pipelines and analytics using Python, SQL, Power BI or Tableau, and partners with 2LOD and Data Engineering teams on root-cause analysis and remediation. Also owns the Financial Crime data and analytics roadmap and presents risk-tolerance performance at governance forums.

Power BI · Tableau · AWS +2

• United Kingdom
• Remote
• Senior

Builds production-quality C++ components, APIs and integrations for NVIDIA's AI-powered developer-tools ecosystem, connecting native C++ tools to the Genie knowledge service via Python, MCP and REST APIs. Also contributes to agentic workflows, retrieval and ingestion pipelines, evaluation infrastructure and enterprise integrations, mentoring engineers and driving initiatives from exploration to deployment.

MCP · REST APIs · Python +3

• Switzerland
• Remote
• Senior
• Permanent

Builds production-quality C++ components, APIs and integrations for NVIDIA's AI-powered developer-tools ecosystem, connecting native C++ tools to retrieval and agentic services via Python, MCP and REST. Involves systems architecture, concurrency, performance optimisation, mentoring and driving initiatives from exploration to production.

MCP · REST APIs · Python +2

• London
• Hybrid · 3 days in office
• Lead · manages people

Lead a team of biologists in the Exploratory Sciences group, owning in vitro pharmacology strategy for novel modalities such as TPD, molecular glues and peptides. Design screening cascades and quantitative assays, set ML-ready data standards, and champion LLM agentic workflows alongside ML and engineering colleagues.

SPR · GCI · nanoDSF +5

• London
• Hybrid
• Mid-level · manages people
• Permanent

Lead and grow a London-based engineering team building real-time safety and oversight systems for AI agents, including the Auto-review permission-boundary model. The role blends hands-on technical work—shaping architecture, reviewing designs, debugging, and coding—with hiring, coaching, and setting the operating cadence. It is highly cross-functional, partnering with alignment researchers, product, security, and infrastructure teams.

OpenAI

• London
• Hybrid
• Senior
• Permanent

Owns the end-to-end release cycle for autonomous-driving AI models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.

GitHub · Buildkite · CLI

• London
• Hybrid · 3 days in office
• Senior

Hands-on in vitro pharmacologist designing and running biochemical, biophysical and cellular assays for novel modalities, generating ML-ready datasets that both advance drug programmes and improve predictive models. Works closely with ML and computational colleagues, using LLM agentic workflows and in silico hypothesis building, and coordinates wet-lab studies across CRO partners.

SPR · GCI · nanoDSF +7

• Cambridge
• Hybrid · 2–3 days in office
• Senior

Work on complex R&D projects within a Modelling Team that trains large self-supervised speech models and deploys them to production. Involves distributed training, transformer architectures, and inference optimisation, with mentoring and cross-department collaboration.

GQA · KV-Caching · Flash Attention +2

• London
• Hybrid · 2–3 days in office

Own the infrastructure behind speech AI models, building scalable data pipelines for ingesting, transforming and validating large training datasets, plus web scraping and data acquisition tooling. Operate the platform that trains, evaluates and serves models in production, optimising GPU utilisation, scheduling and observability across distributed systems.

Docker · Kubernetes