Senior AI Engineer
You will work with Python, LangChain, LangGraph, vector databases, Docker, Kubernetes, and cloud platforms (Azure, AWS, GCP) to design and deploy production-grade AI applications. The company builds scalable, enterprise AI systems using LLMs, agentic workflows, and RAG architecture for clients in finance, retail, healthcare, and other industries. You will operate within small, high-performing delivery teams and contribute to technical leadership.
Free Tailor for ATS: 10/10 runs left
Senior 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 a Senior 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).