AI Engineer
AI Engineer
London (Hybrid, typically 1 day per week, but this will occasionally vary slightly)
Opportunities at this level in AI are exceptionally rare. Join one of the true global leaders in the space.
We’re lucky enough to be partnering with one of the world's leaders in Applied AI. They're building the most important solutions at the forefront of commercial Generative AI deployment and answering the global demand for useful, tangible AI products.
The business designs and delivers production-grade AI systems for large, market-leading clients across various industries, including financial services, retail, healthcare, travel, gaming, and critical infrastructure. Their teams work directly with globally recognised brands to build scalable AI applications that solve real operational problems, not proof-of-concept demos.
This is a highly technical, engineering-led environment focused on shipping real-world AI systems into production. The culture is fast-moving, collaborative, and deeply product-minded, with strong emphasis on ownership, experimentation, and engineering quality.
The company is entering a major phase of international growth and investment, with significant backing, ambitious hiring plans, and access to some of the most advanced AI capabilities currently available in the market.
The Role
As an AI Engineer, you’ll work within small, high-performing delivery teams designing, building, and deploying enterprise-grade AI applications powered by Large Language Models and modern AI tooling.
You’ll operate across the full delivery lifecycle from solution architecture and orchestration through to deployment, optimisation, monitoring, and client adoption. Projects are highly hands-on and often involve agentic systems, retrieval architectures, multimodal workflows, and real-time AI applications deployed into complex enterprise environments.
This role combines strong software engineering with applied AI delivery. You’ll be expected to contribute technically, communicate directly with clients, and help shape engineering best practices internally.
Key Responsibilities
- Design and build production-grade AI applications using LLMs and modern AI frameworks
- Develop scalable backend systems, APIs, orchestration layers, and microservices to support enterprise AI deployments.
- Work across the full AI lifecycle including architecture, deployment, monitoring, evaluation, optimisation, and maintenance
- Build and deploy agentic workflows, RAG systems, multimodal applications, and AI-powered automation tools
- Collaborate directly with enterprise stakeholders to understand business problems and translate them into technical solutions
- Contribute to technical leadership across projects, including mentoring engineers and improving internal engineering standards
- Work closely with cross-functional teams across engineering, product, delivery, and client environments
What We’re Looking For
- Strong software engineering foundations, particularly in Python
- Experience building and deploying production AI/ML systems in enterprise environments
- Hands-on experience with Large Language Models and modern AI application architectures
- Strong understanding of backend engineering, APIs, microservices, distributed systems, and cloud-native development
- Experience with technologies/frameworks such as LangChain, LangGraph, vector databases, Docker, Kubernetes, Azure, AWS, or GCP
- Ability to design scalable, maintainable systems with strong engineering and operational awareness
- Strong communication skills and confidence operating in client-facing environments
- Comfortable working in fast-paced, high-ownership engineering teams
- Experience across the full lifecycle of AI delivery from ideation through to production deployment is highly desirable
Desirable Experience
- Agentic AI systems and orchestration frameworks
- RAG architectures and evaluation frameworks
- Real-time or voice-enabled AI systems
- Production monitoring, guardrails, latency optimisation, and cost optimisation
- Previous experience in consulting or highly collaborative delivery-focused environments
If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).