Machine Learning Engineer at Intelix.AI, Remote/London, 3 Months initial, £400-£500 per day

AI / Machine Learning Engineer

Generative AI | Agentic AI | RAG | Production Engineering

Contract | £400-500 per day | Inside IR35

Initial 3 months + extension | London or Manchester | Hybrid - Largely Remote

We are looking for hands-on AI/ML Engineers to support the development of production-grade AI products within a major regulated financial-services environment.

The requirement is for engineers who can build, integrate, test and operate enterprise AI solutions not candidates whose experience is limited to research, notebooks or chatbot prototypes.

Key responsibilities

• Design and build production AI, Generative AI and Agentic AI applications
• Develop RAG pipelines, agent workflows and enterprise knowledge integrations
• Build APIs and services using Python and modern backend frameworks
• Integrate AI capabilities with internal systems, data platforms and business workflows
• Implement evaluation, observability, guardrails and human-in-the-loop controls
• Support deployment through CI/CD, cloud platforms and containerised environments
• Work closely with Product Managers, Technical BAs, Architects, Data and Risk teams
• Contribute to testing, operational readiness and production support

Essential experience

• Strong Python and software-engineering capability
• Production AI/ML, LLM, RAG or Agentic AI delivery experience
• Experience with APIs, microservices and system integration
• Cloud experience across Azure, AWS or GCP
• Familiarity with frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen or similar
• Understanding of model evaluation, observability, security and governance
• Docker, Kubernetes, CI/CD or infrastructure automation experience
• Private-sector delivery experience is essential
• Banking or financial-services experience is highly desirable

We are particularly interested in engineers who understand that production AI requires reliability, monitoring, controls and operational ownership not just model accuracy.