AI Native Software Engineer – Agentic & Applied AI

If you’ve built AI systems that made it into production, we’d like to hear from you.

We’re looking for AI Native Software Engineers to join our AI Engineering team in London & Birmingham, working across Agentic and Applied AI.

We’re hiring across different levels of experience, so the scope and seniority of the role will depend on your background, technical depth and level of ownership.

As an AI Native Software Engineer, you’ll design, build and deploy production-grade software and AI systems, working closely with engineering teams to turn AI capabilities into reliable solutions that work in real-world environments.

Depending on your experience, you could be working on:

• Designing and deploying production-grade agentic and multi-agent systems
• Building RAG pipelines, including embeddings, chunking, vector search and context engineering
• Integrating LLM APIs across providers such as OpenAI, Anthropic, Vertex AI and open-source models
• Building orchestration, tool invocation, routing and memory capabilities
• Developing evaluation frameworks and measuring accuracy, latency, cost and safety
• Implementing LLMOps practices including prompt versioning, observability and production monitoring
• Building APIs, backend services and full-stack applications that connect software systems with AI and agentic backends
• Designing and deploying cloud-native solutions using technologies such as Docker, Kubernetes, CI/CD and infrastructure as code
• Using AI-assisted development throughout the software delivery lifecycle, including coding, testing, debugging and code review

For more senior engineers, the role also involves owning technical design, shaping agentic architecture, establishing engineering standards, leading client engagements and mentoring or managing engineering teams.

We’re particularly interested in engineers who can demonstrate real delivery experience . We want to understand what you personally designed, built and deployed, the technical decisions you made, and how you handled the challenges that came with running AI systems in production.

• Strong software engineering fundamentals are essential, particularly in Python, Java or TypeScript .
• Experience with LangGraph, CrewAI, AutoGen, LangChain or equivalent agentic frameworks is highly relevant, but we’re interested in depth of experience rather than simply familiarity with a particular tool.

If you’re a Software Engineer, AI Engineer, ML Engineer or Applied AI Engineer and this sounds like the kind of work you’ve been doing, I’d be interested in hearing from you.

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