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.

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.

Synthesia · London

Owns the multi-quarter strategy for two connected domains, Surveys and Guidance, inside a zero-to-one agentic AI bet on real-time practice and readiness proof. Sets success metrics tied to retention, expansion and revenue, works closely with enterprise customers, and writes strategy docs and PRDs. Hybrid role based in the London office.

Salt Search · London · £70,000 – £100,000 pa

Build and scale a cloud-native AI platform for real-time video security, working across Go and Python backend services and React/TypeScript frontends. You'll design APIs and distributed systems handling real-time video and sensor data, collaborating closely with product and ML engineers and owning features from design to production.

Interface Recruitment · Leeds

Lead a team of four to own the innovation agenda at an FCA-regulated asset manager, translating technology strategy into actionable roadmaps and championing AI, machine learning, generative AI and intelligent automation. Oversee innovation governance, value realisation and risk management, partnering with business, risk and technology teams to strengthen operational resilience within regulatory expectations.

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.

Flarebright · Bicester · £39,000 – £49,000 pa

Contributes across the full development lifecycle, from concept and algorithm design to system integration, testing and troubleshooting of safety-critical navigation and autonomy software in C++. Works with a multidisciplinary team on real-time embedded systems, hardware/software-in-the-loop testing and flight test activities, producing design documentation and test reports.

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.