Production AI Engineer – Enterprise LLM Apps (Hybrid)

Kairos AI Talent; Greater London; Hybrid; GBP 108,000 - 132,000; Full time

Benefits offered by this job

Bonus

Job summary

Kairos AI Talent is seeking a Forward Deployed Engineer for our London hybrid setting. You will design and deploy production-grade LLM and agentic solutions directly with enterprise clients, integrating with existing architectures.

The role emphasizes deep client interaction and high-impact delivery. You will own full-stack delivery from architecture to production, mentor others, and shape technical strategy for scalable, reliable systems.

Qualifications

• Several years of commercial software engineering experience with AI/ML.
• Experience deploying production-grade LLM/agentic applications, not just demos.
• Strong backend, microservices, APIs, CI/CD and modern frontend engineering capability.
• Comfortable working directly with enterprise stakeholders and solving ambiguous technical problems.

Responsibilities

• Design production AI agents and LLM applications using LangChain, LangGraph and LangSmith.
• Develop scalable backend services, APIs, orchestration pipelines and modern web interfaces using Python, Node.js, Java and React/Next.js.
• Apply TDD, CI/CD, pair programming, continuous refactoring and mentor other engineers.
• Independently own full-stack project delivery from architecture through to production deployment.
• Drive technical strategy, define system architecture across scalability, reliability and observability.

Skills

GenAI Foundations

Production AI

Full-Stack Engineering

Client Engagement

Tools

LangChain

LangGraph

LangSmith

CI/CD

Job description

Kairos AI Talent is seeking a Forward Deployed Engineer for our London hybrid setting. You will design and deploy production-grade LLM and agentic solutions directly with enterprise clients, integrating with existing architectures.

The role emphasizes deep client interaction and high-impact delivery. You will own full-stack delivery from architecture to production, mentor others, and shape technical strategy for scalable, reliable systems.