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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Deviation Technologies - **Location:** UK (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Django Web Framework, Fault Tolerance, Python (Programming Language), PostgreSQL, Open Source Technology, Software Product Management, Redis, Regression Testing, Search Technologies, AI Infrastructure, Cloud Platform System, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Prompt Engineering, Model Validation, Caching, Backend, Fastapi, Event Driven Architecture, Build Management, Kubernetes, Low Latency, Machine Learning Operations, Restful APIs, Docker - **Published:** May 31, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=b16dd57fc36fab8d ## About the Role Do you have experience in Python?, Do you have a Master's degree?, We're looking for senior-level engineers with strong production experience. You should have: * Strong commercial experience building and operating production backend systems. * Excellent Python engineering skills. * Experience with FastAPI, Flask, Django, or similar backend frameworks. * Hands-on experience building LLM applications, RAG systems, AI agents, or AI workflow platforms. * Strong understanding of AWS services. Azure experience is also acceptable. * Experience with Docker and ideally Kubernetes. * Experience with PostgreSQL and Redis. * Experience with vector databases such as pgvector, Pinecone, Weaviate, Qdrant, Milvus, OpenSearch, or similar. * Practical knowledge of prompt engineering, structured outputs, tool calling, model evaluation, and model optimisation. * Familiarity with LangChain, LlamaIndex, Semantic Kernel, Haystack, or similar frameworks. * Good engineering judgement around reliability, testing, observability, security, and maintainability. Nice-to-Have Skills * Experience in a startup, scale-up, or high-growth technology environment. * Experience building AI products used by real customers or internal teams at scale. * Experience with agentic systems, workflow state, retries, guardrails, and traceability. * Experience optimising LLM workloads for token usage, latency, caching, model routing, and cost. * Experience with open-source models, fine-tuning, embeddings, or model deployment. * Experience with queues, async processing, event-driven systems, or distributed backend architectures. * Strong product sense and the ability to balance technical depth with delivery speed. ## Description As a Senior AI Engineer, you'll design, build, and improve the backend and infrastructure layer behind advanced AI products. You'll work across: * LLM-powered applications * Retrieval-Augmented Generation systems * AI agents and workflow orchestration * Vector search and embedding pipelines * GraphRAG * Prompt engineering and structured outputs * Model evaluation, optimisation, and monitoring * Scalable APIs and production backend systems * AI infrastructure on AWS This role is suited to someone who understands that strong AI engineering is not just about calling a model API. It is about building the surrounding systems that make AI reliable: retrieval, orchestration, evaluation, observability, latency management, cost control, and fault tolerance. Responsibilities * Design and build production-grade LLM applications and AI-powered backend services. * Develop and optimise RAG pipelines, including ingestion, chunking, embeddings, retrieval, reranking, and response generation. * Build AI agents and workflows that can use tools, call APIs, handle state, and operate within clear reliability constraints. * Create scalable APIs and backend services using Python and FastAPI or similar frameworks. * Work with vector databases, PostgreSQL, Redis, and cloud-native infrastructure. * Integrate LLM providers, embedding models, orchestration frameworks, and evaluation pipelines. * Improve system performance across latency, cost, throughput, reliability, and model quality. * Build evaluation frameworks for LLM outputs, including golden datasets, regression tests, human review loops, and production monitoring. * Make architecture decisions around AI infrastructure, backend design, observability, and deployment. * Own features and systems from design through to production operation. * Collaborate closely with product, engineering, and leadership teams to turn ambiguous AI product ideas into robust technical systems. ## Related Videos - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [HTTP headers that make your website go faster](https://www.wearedevelopers.com/videos/1676-http-headers-that-make-your-website-go-faster) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Event based cache invalidation in GraphQL](https://www.wearedevelopers.com/videos/433-event-based-cache-invalidation-in-graphql) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)