18 of 18 Contract Retrieval-Augmented Generation Jobs in London

NEW CONTRACT AI/ML ENGINEER VACANCY AVAILABLE - HYBRID LONDON Exciting Opportunity with a Cutting-Edge AI Company Contract AI Engineer (LLMs/LangGraph/RAG) 6-Month Initial Contract + extension £350-450 Outside IR35 (competitive) To apply please email WHO WE ARE We're working with an innovative organisation at the forefront of AI-powered solutions, focused on … THE ROLE We're seeking AI Engineers to design, build, and deploy conversational AI products using LangGraph, OpenAI functions, and Retrieval-Augmented Generation (RAG) techniques. You'll be part of a hands-on team delivering high-performance AI tools in a fast-paced environment. WHAT YOU WILL BE DOING Building conversational AI flows with … LangGraph and OpenAI function-calling Integrating live data (e.g., sports data, betting odds) into real-time chat systems Developing memory handling, tool usage, and RAG pipelines Collaborating on system design, prompt tuning, and architecture decisions Optimising AI performance for speed, stability, and user experience WHAT WE NEED FROM YOU Proven experience with LangGraph or LangChain Strong Python skills and experience More ❯

AI/ML ENGINEER VACANCY AVAILABLE - HYBRID LONDON Exciting Opportunity with a Cutting-Edge AI Company (Open to UK-Based candidates) Contract Junior AI Engineer (LLMs/LangGraph/RAG) 6-Month Initial Contract + extension £250-300 Outside IR35 To apply please email WHO WE ARE AI Company sitting in Sports Space. THE ROLE We're seeking AI Engineers … to design, build, and deploy conversational AI products using LangGraph, OpenAI functions, and Retrieval-Augmented Generation (RAG) techniques. You'll be part of a hands-on team delivering high-performance AI tools in a fast-paced environment. WHAT YOU WILL BE DOING Building conversational AI flows with LangGraph and OpenAI function-calling Integrating live … data (e.g., sports data, betting) into real-time chat systems Developing memory handling, tool usage, and RAG pipelines Collaborating on system design, prompt tuning, and architecture decisions Optimising AI performance for speed, stability, and user experience WHAT WE NEED FROM YOU Proven experience with LangGraph or LangChain Strong Python skills and experience working with LLMs Familiarity with RAG pipelines Experience More ❯

problem-solving skills and the ability to work autonomously in a dynamic environment. DESIRABLE SKILLS Experience supporting LLM training or retrieval-augmented generation (RAG). Familiarity with feature stores, vector databases, or embedding pipelines. Understanding of data quality, lineage, and governance best practices. Exposure to cloud platforms (AWS, Azure, or GCP) and distributed compute More ❯

Prompt Engineer (AI & Data) – Junior to ExperiencedRemote work - United Kingdom Competitive day rate AI | LLMs | RAG | Healthcare Tech | Data Engineering Tech for Good | Real-World Impact | Ethical AI We're Hiring: Full Stack Developer for Generative AI ApplicationsAre you a seasoned developer excited about the future of AI? We're looking for a Full Stack Developer with a strong backend … Be Doing Designing, testing, and refining prompts for LLMs (OpenAI, Claude, etc.) Building prompt libraries and evaluation frameworks Structuring unstructured data (PDFs, notes, forms) into usable formats Working with RAG pipelines and vector databases (FAISS, Pinecone, etc.) Embedding LLMs into user-facing healthcare tools (e.g., AI assistants, in-context help) Collaborating with product, design, and clinical teams to ship real … and prompt engineering (OpenAI, Anthropic, etc.) Familiarity with structured (SQL, JSON, CSV) and unstructured data Exposure to vector stores and retrieval-augmented generation (RAG) Strong Python skills and comfort working with APIs and data pipelines Bonus: experience in healthcare, accessibility, multilingual interfaces, or regulated environments Why Join? Work on AI that actually helps people More ❯

modular platforms within regulated environments. Implement full lifecycle of AI and GenAI systems using modern architectural approaches, including LLM optimization, Retrieval-Augmented Generation (RAG), and agent-based design. Create and customise risk frameworks, taxonomies, and control libraries aligned with MRM, CRO, and CDO functions. Embed responsible AI principles into system design, control mechanisms, audit More ❯

secure cloud development practices and IAM role design. Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch). Exposure to contact centre automation, conversational agents, or RAG pipelines. Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities More ❯

team building scalable GenAI solutions, architect Agentic AI components, and integrate them into enterprise systems.Skills- Strong experience in full-stack and cloud-native engineering (Azure preferred) Expertise in GenAI (RAG, prompt engineering, LLM APIs) Deep knowledge of Agentic AI systems and orchestration Proficiency in Python, SQL, NodeJS (React is a plus) Agile leadership and stakeholder collaboration skills Details- 6 month More ❯

secure cloud development practices and IAM role design. · Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch). · Exposure to contact centre automation, conversational agents, or RAG pipelines. Please click here to find out more about our Key Information Documents. Please note that the documents provided contain generic information. If we are successful in finding you an More ❯

a day In order to be considered for this role you will need to have - Python, SQL, Unix, Cloud (AWS preferred) LLM applications: LangChain, Pydantic-AI (similar frameworks), RAG systems, MCP servers Front end: some experience with Typescript, REACT Application servers, web servers, database servers, docker Some context: frontend (TS/React) and a backend (Python/FastAPI) leveraging a More ❯

working with a small, agile team focused on deploying open-source models into production environments.?? Key Responsibilities Fine-tune and evaluate LLMs for domain-specific tasks Build and optimise RAG pipelines using vector databases Develop prompt engineering strategies and orchestration flows Integrate models into backend services via APIs Implement evaluation frameworks for response quality and reliability Essential Skills Strong Python More ❯

of machine learning AI/ML pipelines and fine-tuning pipelines to adapt foundation LLMs to enterprise-specific datasets• Work with embedding models and OCI Vector Database to implement RAG Solutions.• Provide technical guidance and best practices around MLOps, model versioning, deployment automation, and AI governance.• Collaborate with functional SME’s, application teams, and business stakeholders to identify AI opportunities More ❯

and semantic reasoning. Leverage ontologies to enhance data pipelines and enable advanced knowledge engineering solutions. Collaborate with AI teams to ensure ontology structures efficiently support Agentic AI applications, including RAG pipelines and Agent Orchestration. Graph Database Expertise Work with both Semantic Graph and Property Graph technologies, understanding their unique architectures and use cases. Utilize Semantic Graph tools for rule-based … standards for Property Graphs. Ability to mentor and train junior team members, fostering a culture of learning and growth. Experience integrating AI considerations (like LLM-based retrieval, RAG pipelines, and Agent Orchestration) into graph ecosystem design. Preferred Qualifications Experience with data pipelines and integrating graph databases into larger data ecosystems. Knowledge of rule-based inference systems and network More ❯

and help lay the foundations for their Agentic AI Journey. What you'll do: Architect and deploy robust, multi-agent systems using Google's ADK Design and implement advanced RAG pipelines to provide agents with deep contextual understanding Design, build, and maintain a suite of secure and scalable Model Context Protocol MCP servers Own the full lifecycle of agent development … from initial design and prototyping to deployment, monitoring, and continuous improvement Experience required: Proven background in similar AI/ML Roles Strong proficiency in Python & SQL Demonstrable experience with RAG, Agentic AI, Googles ADK (Or similar LLM Application frameworks), API Design & Consumption Contract details: 3 Month initial engagement - extensions possible Hybrid - 3 days p/w in Central London Outside More ❯

support secure, air-gapped AI deployments, with a focus on NLP-based tooling * Develop pipelines for transcription ingestion and real-time analytical insight generation * Support graph and RAG-based inference layers using data from structured and unstructured sources * Build and expose APIs for frontend consumption, enabling natural-language querying, dynamic visualisation, and reporting * Ensure system portability via containerisation More ❯

part of a small, elite, cross-functional team. What You’ll Be Doing: Designing and implementing NLP pipelines for transcription, topic extraction, and summarisation Developing modular LLM workflows (e.g., RAG, graph-based reasoning) optimised for low-resource deployments Integrating structured and unstructured data: transcripts, policy documents, supply chain models Collaborating with platform engineers to containerise models for edge inference Defining … experience building and deploying NLP/LLM solutions, including summarisation, entity extraction, and topic modelling Strong Python skills with libraries such as HuggingFace Transformers, spaCy, PyTorch/TensorFlow, or RAG frameworks Experience with knowledge graphs, GNNs, or graph-enabled retrieval Proven ability to optimise ML systems for air-gapped, low-compute, or edge environments Understanding of evaluation methods More ❯

Doing: Architecting and implementing secure backend services to support AI deployments in classified settings Developing transcription ingestion pipelines and real-time insight generation capabilities Supporting graph and RAG-based inference pipelines using structured and unstructured data Exposing robust APIs for frontend engineers to deliver interactive dashboards and NLP-driven workflows Ensuring system portability via containerisation (Kubernetes, Docker) Collaborating … of Postgres or similar databases Proven experience building real-time or batch AI/ML pipelines with strong API design (Bonus) Exposure to LLMs, vector databases, transcription pipelines, or RAG systems (Bonus) Prior work in Defence, aerospace, or national security environments Why This Project? This isn’t another generic SaaS deployment. You’ll be building backend systems that enable critical More ❯

high-performance services using Golang in secure environments Develop ingestion and processing pipelines for transcription and structured/unstructured data Contribute to intelligent data flows including graph-based and RAG inference pipelines Expose well-structured APIs to support real-time dashboards and NLP workflows Deploy and scale systems using Kubernetes and Docker Collaborate with platform and data science teams to … orchestration tooling (e.g. Argo), and Kafka or equivalent Strong database knowledge (Postgres preferred) Ability to design and scale APIs and backend pipelines for data-rich environments Bonus: Familiarity with RAG pipelines, transcription tooling, vector DBs, or LLM deployment Bonus: Prior experience within Defence, aerospace, or highly regulated industries Why It Stands Out: This isnt a generic software build. Youll help More ❯

high-performance services using Golang in secure environments Develop ingestion and processing pipelines for transcription and structured/unstructured data Contribute to intelligent data flows including graph-based and RAG inference pipelines Expose well-structured APIs to support real-time dashboards and NLP workflows Deploy and scale systems using Kubernetes and Docker Collaborate with platform and data science teams to … orchestration tooling (e.g. Argo), and Kafka or equivalent Strong database knowledge (Postgres preferred) Ability to design and scale APIs and backend pipelines for data-rich environments Bonus: Familiarity with RAG pipelines, transcription tooling, vector DBs, or LLM deployment Bonus: Prior experience within Defence, aerospace, or highly regulated industries Why It Stands Out: This isn’t a generic software build. You More ❯