Staff Applied AI Engineer

kadence; Greater London; Sur place; GBP 90 000 - 150 000; Plein temps

Résumé du poste

Kadence is assembling a new Applied AI engineering team in the UK. You will join as a hands-on software engineer with ownership of production AI systems, from design through deployment to monitoring and continuous improvement.

Expect deep work in areas like agentic systems, evaluation, AI platform lifecycle, and retrieval, with emphasis on production readiness and real-world performance.

Qualifications

• Strong production Applied AI experience
• Experience taking AI systems from prototype to production
• Attention to scalable backend APIs and distributed systems
• Familiarity with agent frameworks and tool calling concepts
• Experience with CI/CD, cloud infra and observability
• Ability to own and improve end-to-end AI lifecycle

Responsabilités

• Architect, build and deploy production-grade AI systems
• Own lifecycle from data ingestion to monitoring and iteration
• Collaborate with platform and ML teams to improve reliability

Connaissances

Python

C#

Production AI

Backend APIs

Distributed systems

CI/CD

Cloud infrastructure

Observability

Outils

LangGraph

MCP

LangFuse

LangSmith

Braintrust

Phoenix

Description du poste

We’re partnering with a growing enterprise software company that is building out a new Applied AI engineering team in the UK.

We’re looking for experienced engineers who have gone beyond AI prototypes and have built, deployed, and improved LLM/AI systems in production.

What you'll work on

Depending on your background, you'll have the opportunity to specialize in areas including:

• Agentic Systems – production agents, tool calling, MCP, orchestration and human-in-the-loop workflows
• Evaluation & Measurement – eval frameworks, golden datasets, LLM-as-a-Judge, regression testing and observability
• AI Platform & Lifecycle – scalable AI infrastructure, model/provider management, monitoring and production reliability
• Knowledge & Retrieval – RAG, hybrid search, reranking, knowledge graphs and semantic models

What we're looking for

We're looking for strong software engineers with meaningful production Applied AI experience. You don't need to be an expert across every area above, but should have deep experience in at least one.

Relevant experience may include

• Python and/or C#
• Production LLM, RAG or agentic systems
• Backend APIs and distributed systems
• LangGraph, MCP or similar agent frameworks
• Langfuse, LangSmith, Braintrust or Phoenix
• CI/CD, cloud infrastructure and observability

Most importantly, we're looking for people who understand the full production AI lifecycle - building, deploying, evaluating, monitoring and continuously improving AI systems based on real-world performance.

This is a hands-on engineering role with significant technical ownership and the opportunity to help shape a new Applied AI team from the ground up.

If you've taken AI systems from “it works in a demo” to “it works reliably in production,” we'd love to hear from you.