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.

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

Lead a team of engineers building self-service infrastructure-as-code primitives, architecting large-scale core services and driving cloud cost optimisation across a multi-cloud estate. The role combines people management, on-call ownership and hands-on work with Terraform, Pulumi, Python or Go, Linux and SRE practices, with hybrid working near an office.

CrowdStrike · United Kingdom

As an Associate Consultant on the Platform Professional Services team, you'll act as a trusted advisor helping customers operationalise Falcon Next-Gen SIEM, demonstrating capabilities and shaping a technical roadmap. Day to day you deliver integration services, knowledge transfer on LogScale NGSIEM, and feed customer requirements back to product teams.

Faculty · London

Builds client-facing products that visualise insights from data scientists, working in cross-functional delivery teams within the National Security and AI Safety unit. Owns frontend standards and reusable component libraries across the company, sets up deployment infrastructure, and mentors other engineers. Requires React, TypeScript, ES6, HTML/CSS3 and data visualisation such as d3, with cloud exposure to AWS, GCP or Azure.

Speechmatics · Cambridge

Own the infrastructure behind speech AI models: building scalable data pipelines for ingesting, transforming and validating large training datasets, plus web scraping and automated data acquisition. Also operates the platform for training, evaluating and serving models, optimising GPU utilisation, scheduling and observability across distributed systems.

Scale AI · London

Leads a forward-deployed engineering team acting as the technical bridge between AI capabilities and strategic enterprise customers. Involves designing custom integrations, ETL pipelines and production AI agents, plus prompt engineering, RAG systems and evaluation frameworks, deployed within customer security and compliance boundaries.

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.

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.

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.

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.