Artificial Intelligence Jobs

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.

PhysicsX · Singapore

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 industry challenges into product opportunities, tracking engagement and measuring value. Based in Singapore, bridging advanced AI capabilities and practical engineering applications.

PhysicsX · Singapore

Join a new Singapore research team building physical foundation models for industrial engineering, translating physics challenges into mathematical formulations and training deep learning models on large datasets. You will own research workstreams, run experiments, and communicate results to customers and at publication venues, with a focus on operator learning, geometric deep learning, or generative models for geometry and spatiotemporal data.

Palo Alto Networks · Seville, Spain

Senior individual-contributor role in the Cortex organization, acting as a technical advisor to strategic enterprise customers and C-level security executives. Drives product strategy and roadmap by translating customer problems into requirements, while developing deep expertise in XSIAM, XDR, XSOAR, CNAPP and AI Security. Mentors technical staff and builds reusable architectures and enablement across cross-functional teams.

Faculty · London

Deliver bespoke, production-grade machine learning systems for government and national security clients, spanning the full ML lifecycle from architecture to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, while advising stakeholders and setting deployment standards.

Faculty · London

Build and scale AI-powered systems for public sector clients, owning the full stack from Python/FastAPI backends to TypeScript and React or Vue frontends. Work in cross-functional teams with data scientists and product managers, deploying to AWS, Azure or GCP with Docker and building data pipelines and cloud infrastructure. May require UK Security Clearance and occasional on-site work with government clients.

Avanti Recruitment · Saint Peters, Australia · £80,000 – £100,000 pa

Take technical ownership of a new AI layer within an established SaaS document-processing platform for the legal sector, working closely with a hands-on CTO. Design production AI/ML systems in Python using NLP, LLMs and retrieval approaches, covering architecture, data pipelines, evaluation and monitoring, while providing technical direction and remaining hands-on.

ElevenLabs · London

Builds and operates the platform every product team ships on, running and scaling Kubernetes clusters including GPU clusters for inference and training across cloud and on-prem. Sets up compute, networking, permissions and access, hosts data systems, and builds tooling and automations to make infrastructure self-serve, working hands-on with research, product, security and safety engineers.

OpenAI · London

Builds and scales the infrastructure that trains and deploys AI agents, spanning a novel in-house container orchestration platform, FastAPI and gRPC APIs, and Terraform-managed cloud systems. Works closely with researchers on large-scale training runs and with product teams launching agentic products to hundreds of millions of users.

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.

Wayve · London

You'll design, build and operate shared infrastructure for model access, agent runtimes and observability, taking projects from problem definition through technical design, deployment and ongoing operation. Working with security, IT and engineering teams, you'll create governed access layers, reusable tooling and standards so teams can run AI agents in production without one-off infrastructure.

Medtronic · London · £95,200 – £142,800 pa

Builds and maintains the internal platform tooling that other engineering teams rely on, spanning Infrastructure as Code with OpenTofu, EKS and Helm, CI/CD automation, and observability with OpenTelemetry. Works across software groups to remove developer productivity gaps and supports AI agentic workflows, with technical mentorship expected. Based in London with two to three days a week in the office.

Becrypt Ltd · London

Hands-on principal-level individual contributor leading AI adoption across engineering, product, IT and operations. Designs and builds agentic workflow platforms, AI gateways and Docker-based services using Python, FastAPI, TypeScript, MCP/FastMCP, OpenAI and AWS Bedrock, while owning AI policy, governance and risk frameworks. Also probes AI systems for vulnerabilities and advises leadership on AI strategy.

83zero · London · £75,000 – £90,000 pa

Design and build intelligent Salesforce solutions, integrating AI capabilities such as Einstein, Prompt Builder and Agentforce into platforms and workflows. Work with business, product and engineering teams to translate complex requirements into scalable technical solutions, optimising data models, automation and integrations with enterprise systems using Apex, LWC and APIs.

Scale AI · London

Builds and scales backend systems and APIs that bring large-scale generative AI products to production for enterprise customers. Work spans distributed data systems, model serving, deployment pipelines, and cloud infrastructure across AWS, Azure, or GCP, in close collaboration with ML and product teams. The role centres on reliability, latency, throughput and cost optimisation in hybrid and multi-cloud environments.