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Hiring: Senior AI Engineer (LLMs, Agents, RAG)
Location: Remote (UK or Canada)
Type: Full-time | Permanent
Salary: Up to £130,000 or $240,000 Canadian

Are you passionate about building real AI systems that get used in production? Interested in LLMs, RAG pipelines, and agentic software, with the freedom to make a real impact?

My client are a well-funded early-stage team helping enterprise clients in regulated sectors deploy scalable AI without overhauling their infrastructure. They focus on performance, maintainability, and fast iteration. No fluff, just outcomes. They're now looking for engineers who want to help shape that future.

Hiring: Senior AI Engineer (LLMs, Agents, RAG)
Location: Remote (UK or Canada)
Type: Full-time | Permanent
Salary: Up to £130,000 or $240,000 Canadian

Are you passionate about building real AI systems that get used in production? Interested in LLMs, RAG pipelines, and agentic software, with the freedom to make a real impact?

My client are a well-funded early-stage team helping enterprise clients in regulated sectors deploy scalable AI without overhauling their infrastructure. They focus on performance, maintainability, and fast iteration. No fluff, just outcomes. They're now looking for engineers who want to help shape that future.

• Building and optimising RAG pipelines including chunking, embeddings, and vector search

• Creating full LLM integrations using OpenAI, Hugging Face, and orchestration frameworks

• Developing robust AI agent systems with tool chaining and multi-step logic

• Building real-time frontend interfaces using React, Next.js, and Vercel AI SDK

• Containerising services using Docker and deploying to AWS (ECS, Lambda)

• Collaborating with researchers to productionise transformer models (e.g. PyTorch, HF)

• Using observability tools like Langfuse to monitor prompt and model performance

• Writing clean, modular, testable code that scales in production environments
  

• 3+ years' experience as a full-stack engineer with strong Python skills

• Proven track record with LLMs, agentic systems, and RAG pipelines

• Experience with vector databases, embeddings, and semantic search

• Solid grasp of prompt engineering and LLM integration best practices

• Familiarity with containerisation, API design, and modern ML deployment tools
  

• Experience with PyTorch or model fine-tuning

• Open-source contributions to LLM or AI infrastructure tools

• Experience with Elasticsearch or OpenSearch for retrieval

• Familiarity with Terraform, GitHub Actions, or infrastructure automation

• Built doc processing pipelines involving PDFs, HTML, or structured data

• Interest in async workflows and distributed data processing

If you're ready to work on meaningful, high-impact AI problems in a fast-moving team, we'd love to hear from you.

Apply now or drop us a message to chat more.