5 of 5 Retrieval-Augmented Generation Jobs in Birmingham

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯

Solid understanding of REST APIs, cloud platforms (Azure/AWS/GCP), and agile delivery A passion for clean code, scalability, and technical excellence Nice to Have Experience with RAG systems, multi-agent AI, or Langfuse/LiteLLM Python proficiency for AI/ML integration Familiarity with MLOps and cost optimisation for AI systems Background in B2B SaaS or financial More ❯

Studio or custom frameworks). Clear judgment around latency, cost, and reliability trade-offs. Track record of mentoring and raising engineering standards. Nice to have: Retrieval pipelines, RAG evaluation, Kubernetes, CI/CD for ML, and enterprise security exposure. More ❯

Generative AI solutions using Azure AI Foundry, Azure OpenAI and Azure ML. Collaborate with clients to define use cases and translate business needs into technical solutions. Building and implementing RAG pipelines and fine-tuning models. Presenting technical concepts to both technical and non-technical stakeholders. Contributing to agile delivery processes and sharing knowledge through workshops and demos. To be successful More ❯

We’re looking for a DevOps Engineer who’s excited about building the infrastructure behind next-generation AI products. You’ll join a small, experienced team developing an internal Kubernetes-based platform that enables AI innovation across the organisation automating everything from deployments to observability, and helping developers build smarter applications with confidence. What you’ll be doing … environments Managing Infrastructure as Code with Terraform and improving GitOps workflows (ArgoCD/GitHub Actions) Building observability and monitoring stacks using Prometheus, Grafana, and Loki Supporting AI workloads (LLMs, RAG, and document processing applications) running on Kubernetes Automating platform operations with Python, Go, and shell scripting Implementing security guardrails, PII compliance tooling, and best practices for production AI systems What More ❯