20 of 20 Remote/Hybrid Retrieval-Augmented Generation Jobs in the South East

services, APIs and integrations with existing platforms Implement data pipelines, embeddings, vector search and retrieval-augmented generation (RAG) patterns Work closely with engineering, product and business stakeholders to shape AI use cases Ensure solutions meet security, governance and performance requirements Contribute to best practice … with vector databases, embeddings and modern AI architectures Comfortable working in agile, fast-moving delivery environments Nice to Have Experience with GenAI use cases (RAG, agents, copilots, document automation) Exposure to MLOps , CI/CD and monitoring of AI systems Experience in regulated or enterprise environments Consulting or client-facing ...

experience with: Production-level LLM applications including fine-tuning and customisation Function-calling systems or retrieval-augmented generation (RAG) architectures Full-lifecycle projects from prototyping to production Mentoring junior engineers or shaping technical direction within teams What You’ll Gain A high-impact role … with visibility and technical influence The opportunity to shape the next generation of AI platforms Hybrid working with three days per week onsite in Oxfordshire and two days remote A supportive team that values experimentation, clean engineering and continuous learning A salary ...

intelligent, distributed systems Architecting and building AI-driven capabilities , including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) AI agents and orchestration workflows Designing and maintaining backend services and APIs (primarily Python, FastAPI/Flask) Building and scaling data pipelines and search systems using … Python or similar languages Significant experience with backend development , microservices, and distributed systems Hands-on experience with AI/ML systems , including LLMs, RAG, or vector databases Solid understanding of containerisation and orchestration (Docker/Kubernetes) Experience delivering secure, on-premise or regulated systems Proven ability to lead technically , mentor ...

Experience deploying and managing applications with Azure and Docker. • Familiarity with frameworks like LangChain and Retrieval-Augmented Generation (RAG) models for AI-driven applications. • Experience with pandas for data manipulation. What’s on offer • Regular salary reviews recognising performance and contribution. • Generous annual leave ...

Balancing cost, performance, and reliability Applied AI Working with Azure OpenAI APIs beyond prompt demos Retrieval-augmented generation (RAG) Embeddings, vector stores, and evaluation Guardrails, rate limiting, and failure handling Human-in-the-loop workflows Integration & automation Integrating AI into existing enterprise systems Automating ...

party vendors. Knowledge of OO programming and software design, i.e., SOLID principles. Knowledge and working experience of AGILE methodologies. Familiarity with Databricks, and RAG application architecture a plus Experience with latency optimisation and quantisation preferred Additional Information What’s in it for you?: Competitive salary that reflects your skills, experience ...

ideal for someone who excels at technical storytelling and enjoys translating complex concepts-such as retrieval-augmented generation (RAG), vector search, and large language model (LLM) integrations-into engaging, developer-focused multimedia content. You will play a key role in shaping video strategy, producing … curate a content calendar with a strong focus on video and demo assets Script, produce, and edit technical videos (e.g. step-by-step RAG demos, vector search walkthroughs, LLM integration tutorials) using tools such as Camtasia or similar Collaborate closely with engineers, developer advocates, and demo creators to ensure technical ...

following skills and experience: Strong Python and SQL experience, ideally with Databricks Experience with ML and LLM tools (e.g., scikit learn, XGBoost, PyTorch, TensorFlow, RAG, APIs) Comfortable with data engineering basics and MLOps practices Experience working with cloud platforms such as Azure, AWS, or GCP Benefits The successful Senior ...

microservices or serverless architectures Practical exposure to machine learning plus generative AI models including LLMs SLMs vision models Familiarity with AI frameworks such as RAG LangChain LlamaIndex plus agentic frameworks Hands-on cloud experience within Azure or AWS plus CI/CD tooling and Git Desirable Skills ...

including AI and ML services Solid foundation in software engineering principles for scalable, production-grade systems Experience designing and delivering enterprise AI solutions including RAG-based architectures using vector databases Proven experience delivering full-stack AI or ML systems within enterprise environments Strong understanding of advanced agent architectures, reasoning systems ...

APIs, JSON and spatial query engines (e.g. Apache Spark) Experience with Generative AI technologies including Large Language Models (LLMs), Retrieval Augmented Generation (RAG) and Prompt/Context Engineering Passion for continuous improvement and delivering high-quality solutions The Rewards We want you to love ...

/ML solutions in production Strong programming skills in Python and SQL Experience with classical machine learning and LLMs/generative AI (prompting, RAG, APIs) Solid software engineering fundamentals Experience working with cloud platforms Benefits The successful Senior AI Engineer will receive the following benefits: Salary ...

patterns, and agile delivery practices Experience with geospatial data, REST APIs, JSON, and spatial engines (e.g., Apache Spark) Experience with Generative AI, including LLMs, RAG, and prompt/context engineering A passion for continuous improvement and delivering high-quality solutions The Rewards We want you to love what you do. ...

Python and JavaScript Hands-on experience with backend frameworks and modern frontend frameworks Deep knowledge of Generative AI and agent-based AI frameworks including RAG and orchestration patterns Strong experience working with vector databases and AI-specific data stores Solid understanding of AI and ML models, LLMs and generative ...

TypeScript-based applications Understanding of semantic/graph data (e.g., RDF triples, SPARQL , Amazon Neptune ) Ability to validate AI-supported features, including LLM/RAG behaviours via Amazon Bedrock Knowledge of performance testing for serverless architectures and WCAG 2.2 AA accessibility Familiarity with GDS Standards and testing in the public ...

solutions that improve operational efficiency, regulatory compliance, and customer trust while leveraging advanced analytics and automation. Your Responsibilities Design, develop, and optimize RAG-based solutions integrating retrieval systems with large language models. Build and maintain applications using LangChain to orchestrate complex AI workflows. Implement and manage vector databases … scalable AI-powered applications. Fine-tune and evaluate large language models for specific use cases and domain adaptation. Optimize retrieval and generation workflows for performance, accuracy, and cost-efficiency. Stay updated on the latest advancements in generative AI, retrieval techniques, and vector search technology. ...

Agentic AI solutions aligned to real business workflows Build and orchestrate autonomous agents with planning, reasoning, and tool use Develop LLM-driven systems including RAG, Q&A, and enterprise copilots Integrate GenAI into existing platforms, products, and processes Own delivery end-to-end: design through to production Work closely with … Generative AI and LLMs Agentic AI frameworks such as LangGraph, AutoGen, or CrewAI Python with modern AI libraries (LangChain, Hugging Face, PyTorch) Experience building RAG pipelines and knowledge retrieval systems Cloud platforms: Azure, AWS, or GCP Microsoft/Azure (Highly Desirable) Microsoft AI Foundry Azure AI Agent Service ...

that enhance global sales workflows. Build scalable backend services and full-stack applications for internal teams. Architect, implement, and optimize LLM orchestration frameworks and RAG-based solutions. Collaborate with cross-functional teams to define requirements and deliver innovative tools. Ensure reliability, scalability, and performance of distributed systems handling massive datasets. … workflows . Strong proficiency in Angular (primary frontend); React optional. Hands-on experience with LangChain, LangGraph, and Indexify , with a deep understanding of RAG architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ...

Skills for the Artificial Intelligence Architect: Proven experience architecting solutions across Generative AI, Agentic AI, machine learning and automation Strong understanding of prompt engineering, RAG pipelines, model tuning, MLOps and LLMOps Experience delivering enterprise-scale RAG solutions using LLMs and vector databases Ability to design AI platforms that integrate with ...

best practices for content analytics. Core Skills & Competencies . Technical Skills: o Experience or interest in NLP and LLM applications (transformers, Retrieval-Augmented Generation, prompt engineering) o Familiarity with data visualization and scientific communication tools o Knowledge graph and ontology management o Python ...