15 of 15 Retrieval-Augmented Generation Jobs in Bristol

gatherings Salary: Senior: €130–150k base + growth trajectory Principal: €160–200k base + package discussion Tech: Python, JavaScript, Azure, AWS, AI, LLM's, RAG Industry: AI Consultancy The Role We're looking for talented engineers to join our customer-facing AI practice, from Senior Forward Deployed Engineers through … components, and solution standards AI Mastery & Innovation Implement AI solutions leveraging LLMs, foundation models, and retrieval-augmented generation (RAG) systems Design evaluation frameworks addressing bias, hallucination detection, and business impact Explore novel AI applications while integrating traditional ML techniques where appropriate ...

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 ...

fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores … ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape ...

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 ...

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 ...

Have Skills: Strong background in application security, cloud security, or security architecture Hands-on experience with securing AI/ML systems, including LLMs, APIs, RAG pipelines, and vector stores Deep familiarity with AI security risks and threat modeling methodologies Working knowledge of modern DevSecOps practices and tools Excellent communication ...

models. Strong experience with transformer models, embeddings, vector search, and Generative AI architectures. Practical experience using Hugging Face, OpenAI, LangChain, Retrieval Augmented Generation, and diffusion models. Strong MLOps experience including MLflow, Kubeflow, Airflow, Docker, Kubernetes, and CI and CD tooling. Strong programming skills … teams and enterprise environments. Desirable Skills Experience with vector databases such as FAISS, Pinecone, or Weaviate. Knowledge of enterprise scale Retrieval Augmented Generation systems. Experience within global manufacturing, engineering, or industrial environments. Understanding of data governance, security, and responsible AI principles. What This Role ...

Centre of Excellence within a consultancy or Microsoft Partner environment. Deep expertise in enterprise AI solution design, including generative AI, Azure OpenAI, Copilot Studio, RAG, cognitive services, and data orchestration patterns. Strong background in the Microsoft ecosystem, especially Dynamics 365, Power Platform, and Azure services. Hands‐on experience shaping ...

Engineer - LLM RAG AWS MLOps – Bristol (Hybrid) I'm working with a fast-growing tech company in Bristol that needs an AI/ML Engineer to build and deploy machine learning and LLM solutions. You'll be working across the full ML lifecycle—from design through to production … doing: Building and deploying ML models and LLM applications Fine-tuning large language models for specific use cases Working with prompt engineering and RAG systems Creating end-to-end ML pipelines—ingestion, feature engineering, deployment Developing LLM-powered tools: chatbots, automation, content generation Implementing MLOps practices: versioning, experiment ...

pipelines, and API services Develop sophisticated prompt engineering strategies for LLM-based features, including few-shot learning, chain-of-thought reasoning, and retrieval-augmented generation Optimize models for specific use cases and performance requirements Design and optimize database schemas for relational database Collaborate with ...

User-Defined Agent Logic: Creating a \"no-code\" engine where users can verbally define workflows and guardrails that the system executes deterministically. Hierarchical & Auditable RAG: Routing queries through complex layers of patient history, clinical guidelines, and organizational policies with full traceability. Resilient Orchestration: Managing long-running conversation states, tool usage … executor patterns and manage shared memory across agents. Prompt Engineering & Optimization: utilize programmatic approaches to compile and iteratively improve prompts based on evaluation metrics. RAG Optimization: Enhance retrieval signal through hybrid search, re-ranking, and query rewriting, ensuring high context precision and recall. Observability & Evals: Build robust tracing ...

capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People … Langchain, AutoML, OCR, STT, feature stores, vector DB. Implementation of AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG, deployment models Building and using cloud-based solutions (networking, security, storage, monitoring, scaling, DR/HA) on one or more cloud platforms SW Engineering ...

work on cutting-edge Generative AI projects that are currently in the research phase and have the potential to shape the next generation of healthcare technology. Due to NDAs, full project details will be shared during an initial conversation — but expect complex, meaningful, and highly innovative AI challenges. … they’re looking for: > 7–8 years’ commercial experience in AI/Machine Learning > Strong hands-on expertise in Generative AI (LLMs, multimodal models, RAG, diffusion models, or similar) > Solid background in healthcare – NHS, medtech, clinical data, medical devices, or regulated environments > Ability to demonstrate the evolution of AI technologies ...