Artificial Intelligence Jobs in London

Isomorphic Labs · London

Translates Isomorphic Labs' security strategy into engineering delivery, steering a multi-quarter InfoSec roadmap spanning Cloud Security, Platform IAM and Secure SDLC. Partners directly with engineering and ML teams to unblock architectural issues, secure drug discovery pipelines and build data-driven dashboards giving the CISO visibility into program health and risk metrics. Reports to the CISO with a functional tie to the TPM Discipline Lead.

Isomorphic Labs · London

Lead the hardening and scaling of an inference platform serving fleets of cutting-edge ML models for scientific applications. Set strategy and roadmaps, architect next-generation services to solve scaling limits, and partner with research, product and operations teams to align infrastructure with biotech R&D cycles.

Databricks · United Kingdom

Customer-facing technical authority on Generative AI, LLMs and applied ML for digital-native and startup accounts across EMEA. Shapes architectures, builds hands-on proofs of concept and reference implementations on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog), and leads fine-tuning and evaluation engagements on open models. Also mentors the field engineering organisation and represents the company externally through talks and blogs.

Synthesia · London

Own the end-to-end Interactive Avatar API, taking it from closed beta to general availability. Define the developer-facing surface (SDK, integration patterns, docs), real-time experience quality, and the commercial model, working closely with engineering, research, and design partners.

Infused Solutions · London · £65,000 – £75,000 pa

Hands-on full-stack role building brand-new AI-powered products from concept to production within a small, senior engineering team. You'll architect scalable solutions, develop PoCs, prototypes and MVPs, build React UIs and Node.js/Express/Python APIs on Azure, and use AI-assisted development tools to accelerate delivery.

Synthesia · Seattle, United States

First Developer Advocate for an AI video platform's API, responsible for writing tutorials and blog posts, building sample apps and starter kits, and producing video walkthroughs and livestreams. Represents the company at conferences, meetups and hackathons while channelling developer feedback back to Product and Engineering, and growing community channels like Discord and a developer newsletter.

Bowers Partnership · London · £825 pd

Hands-on VP-level data scientist building generative AI, LLM/NLP and statistical modelling products end to end, from prototype to production, for a boutique investment bank's M&A and advisory bankers. Works in a small team, writing production-quality Python and explaining models and assumptions directly to senior non-technical stakeholders. M&A experience is essential; hybrid with at least three days a week in the London W1 office.

EMBS Engineering · London · £75,000 – £85,000 pa

Lead a team of AI developers while remaining hands-on, building enterprise-grade Generative and Agentic AI applications for a financial services client. Work spans Python and Java services, FastAPI APIs, LLM integrations, RAG architectures and agent-based workflows on AWS Bedrock, AgentCore and EKS, plus CI/CD and DevOps. Also involves setting engineering standards and mentoring within a consultancy team.

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.

Profile 29 · London · £40,000 – £50,000 pa

Supports founders, developers and customer success on a fundraising SaaS platform, splitting time between customer conversations, writing product requirements, testing features and researching AI applications. Runs sprint planning, monitors feedback and performance, and helps shape 3- and 12-month roadmaps while balancing technical debt against new features.

eFinancialCareers · London

You will partner with portfolio managers, analysts and researchers to understand investment workflows, then design, build and deploy AI-powered applications and data tools for front-office teams. The role sits in a central Data & AI team, integrating large-scale data, machine learning models and modern software engineering practices in a fast-paced hedge fund environment.

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.

PhysicsX · New York, United States · US$240,000 – US$300,000 pa

Leads regional deployment engineering for a physics AI platform, owning end-to-end success of customer-owned infrastructure deployments. Acts as primary technical contact for CIOs and CTOs, overseeing Kubernetes-based platform rollouts, security reviews, and version upgrades while hiring and growing a team of deployment engineers.

Entrust · London

Owns a core area of the document verification platform, setting strategy and roadmap for identity document checks used in onboarding and account opening. Works with Engineering, AI/ML, Data Science, Design, Growth and Compliance to improve verification accuracy, conversion, operational efficiency and fraud prevention, using experimentation and analytics.

Wayve · London

Builds and evolves the data pipeline and orchestration platform behind Wayve's autonomous driving data, revamping the existing Harness system and creating a new DAG-based workflow platform. Works with Python, Airflow/Dagster/Flyte, Ray or Spark and Kubernetes to run hundreds of parallel pipeline steps, batch inference and evaluations reliably at scale.