7 of 7 Remote/Hybrid Retrieval-Augmented Generation Jobs in Chelmsford

build and evolve Generative AI (GenAI) proof-of-concepts (POCs) for clients using techniques like Retrieval-Augmented Generation (RAG) and intelligent agents. Support the transition of these POCs into scalable, production-ready solutions. Contribute to the design and development of full-stack applications ...

based systems (e.g. LangChain, LlamaIndex, AutoGen, custom agent frameworks) Familiarity with prompt engineering, tool calling, retrieval-augmented generation (RAG), and multi-agent workflows Experience integrating AI into real systems, APIs, event-driven architectures, data pipelines, and automation platforms (e.g. UiPath, Blue Prism) Comfortable experimenting ...

/Vertex AI, including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications, leveraging RAG (Retrieval-Augmented Generation), agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop … Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems. Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI. Experience with vector databases and retrieval-based ...

Practical experience with AWS (and ideally Terraform, GitLab CI). Experience with agentic systems or LLM-powered automation (e.g. tool-augmented LLMs, RAG workflows, agents for complex workflows). If this sounds like you, reach ...

where users can query information directly through an integrated AI assistant. The Challenges You'll Work On Evaluating a retrieval-augmented-generation (RAG) system in production without labelled data Designing your own benchmarks from scratch Building an agentic retrieval pipeline that adapts ...

applicants but be currently resident and eligible to work in the UK Demonstrable experience of building and deploying complex AI applications using LLMs, RAG and agentic workflows GraphRAG/Knowledge Graph expertise - deep knowledge with Knowledge Graphs and vector databases Strong technical fluency - TypeScript/React, Langgraph/Langchain, neo4j ...

technical stakeholders GenAI work You will work with GenAI in ways that are grounded in real use cases and business value: Building RAG systems that improve search, content discovery or productivity rather than existing for their own sake Implementing guardrails so models do not leak PII or generate harmful … Experience with PyTorch or TensorFlow GenAI specific Hands on experience with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases such as FAISS, Pinecone or Weaviate Ability to evaluate and improve prompts and retrieval quality using clear metrics Understanding ...