1 to 25 of 29 Retrieval-Augmented Generation Jobs in Slough

techniques. Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such as enhanced personalization, lead qualification, content generation, and workflow automation. Own the end-to-end ML lifecycle: from hypothesis generation, experimentation, evaluation, and explainability, to scalable deployment in production … libraries (PyTorch or TensorFlow). Hands-on experience with LLMs, prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) pipelines. Experience integrating ML models via APIs and embedding AI in enterprise systems. Deep knowledge of cloud platforms (AWS/GCP/Azure) and containerized ...

design, build, and deliver next-generation AI systems. You will work across LLMs, retrieval-augmented generation (RAG), and modern agent frameworks to transform large, unstructured data into meaningful insights and production-ready capabilities. This is a hands-on role within a growing … entity extraction, and intelligent automation. Design scalable data and streaming pipelines capable of handling large, heterogeneous datasets. Build and optimize vector search, embeddings, and RAG systems to support high-quality retrieval. Deliver production-ready APIs, services, and model inference systems. Manage deployment, monitoring, observability, and continual improvement of ML models. ...

digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skills 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 … experience with SAP AI Core, Generative AI Hub, and SAP HANA Cloud Vector Engine (for Retrieval-Augmented Generation, RAG). Proven ability to embed AI and advanced analytics into SAP business processes, leveraging SAP's Business AI suite and integrating external LLMs (e.g., OpenAI ...

Have Experience with multi-modal AI (text, image, audio). Familiarity with vector databases and retrieval-augmented generation (RAG). Background in enterprise architecture frameworks. Why Join? Work on innovative AI projects shaping the future of enterprise solutions. Collaborate with a high-performing team ...

accelerate software development (using Github Copilot Coding Agents or similar) Desirable: Experience with prompt engineering, Retrieval-Augmented Generation (RAG), and graph databases Familiarity with multi-agent LLM systems and agentic platforms (e.g., AutoGen, CrewAI), and experience deploying LLM-based applications Experience with tools such ...

expertise in Python, React, and modern AI/ML development, including LLM frameworks, SDKs, and retrieval-augmented generation (RAG) systems. Key Responsibilities Design and develop scalable full-stack solutions involving both frontend (React/TypeScript) and backend (Python/Java). Build and optimize …/ML pipelines leveraging LLMs and RAG architectures. Develop SDKs and APIs to support AI-driven applications in resource-constrained or production-grade environments. Collaborate across engineering, product, and research teams to drive innovation in AI/ML-based products. Ensure high performance, testability, and reliability across the stack. ...

create high-quality pre-trained datasets, fine-tuned industry-specific Large Language Models(LLMs), and Retrieval-Augmented Generation (RAG) pipelines supported by vector databases. Our innovations can reduce Generative Artificial Intelligence(Gen AI) costs by up to 80% and bring Gen AI solutions ...

foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). Bachelor's or Master's degree in Computer Science, Engineering, or a related ...

Responsibilities Design and implement AI/ML and Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor ...

/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 ...

production in large or complex organizations. Strong understanding of AI and machine learning technologies including natural language processing, generative AI, retrieval augmented generation and MLOps. Hands-on experience with cloud platforms, with a preference for Microsoft Azure. Excellent leadership and communication skills with ...

analyse and summarise technical content into high-accuracy insights and reports • Deliver production-grade AI agent solutions such as intelligent assistants or insight-generation tools • Collaborate with research, engineering and strategy teams to support technical intelligence workflows • Perform any additional duties reasonably required to support project objectives Required … with agent development frameworks such as LangChain, AutoGen, LlamaIndex, etc • Strong proficiency in Prompt Engineering and Context Engineering • Working experience with RAG (Retrieval-Augmented Generation) • Excellent programming skills (Python preferred) • Solid software engineering background with experience delivering production-quality systems Desired Skills • Experience working ...

Architect & Engineer AI Systems: You won't just call an API; you will build robust processing architectures that leverage off-the-shelf LLMs, RAG pipelines, and context engineering to solve hard problems. You will benchmark these systems rigorously to ensure they actually work, not just "feel" smart. Build the Backend ...

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 ...

strong parent-company backing. Key Responsibilities Design and deploy AI features (intelligent search, procurement agents, predictive maintenance). Build and integrate LLM-driven agents , RAG pipelines, and predictive models. Collaborate with software engineers to embed AI securely into production. Define AI standards , select tools, and shape the technical roadmap. Opportunity ...

tools, and enterprise connectors. Skills: 6–8 years in Software/application engineering, AI engineering, or applied data engineering. Strong experience with LLMs, embeddings, RAG, retrieval stacks, and vector stores. Hands-on experience in multi-agent systems, agent orchestration, or MCP-like tool patterns. Proficiency in Python, including ...

sense of ambiguous problem statements. Our client problems can range in a variety of domains. Some examples, but not limited to, are building a RAG leveraging open source or commercial LLMs, building a Multiagent system, leveraging Small Language models that could be locally resident, problems in computer vision, speech, Natural ...

Scala + React/TypeScript * Experience building modern front-end applications Scala + AI * Experience building AI agents using relevant frameworks * Understanding of LLMs, RAG, tool-building, etc. * Ability to design automations and improve processes using AI If you're excited to work in a fast-paced environment where engineers ...

Transformer-based text classification (BERT/DistilBERT/RoBERTa) • Fine-tuning classification heads • Embeddings + cosine similarity search • Supporting LLM-adjacent work (not deep RAG) Tech Python, sklearn, XGBoost/LightGBM, HuggingFace Transformers, BERT-family models, embeddings, cloud-based ML, CI/CD awareness. What They're Looking For • Strong ...

machine learning, and mathematical concepts Proven experience delivering production-grade data science solutions Hands-on experience with modern data science tooling, including LLMs/RAG approaches Advanced SQL skills Experience working in complex, enterprise-scale environments Strong written and verbal communication skills Ability to perform under technical interviews including live ...

gaming/fintech/FS) Curiosity for frameworks and agents that weren't on GitHub yesterday Cloud + MLOps + vector search + RAG = all welcome. Why this is a career move Board-level support — pace, budgets, expectations Chance to define AI engineering standards for a global brand Fast loops ...

NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. ...

from concept through to secure, scalable production deployment. You'll work across engineering, commercial, and operational teams to develop GenAI tools including retrieval-augmented systems, intelligent assistants, and workflow automation. Your work will be central to embedding GenAI into enterprise platforms, unlocking measurable business outcomes while … ensuring maintainability, security, and compliance. Key Responsibilities Lead the design and delivery of production-grade GenAI solutions using LLMs, RAG, and vector search, optimising prompts, context, and retrieval for accuracy and performance. Architect and implement GenAI services integrated with enterprise systems and cloud platforms, ensuring scalability, security ...

LangGraph, and MCP. Build and productionise agentic AI solutions with strong evaluation, observability, and orchestration. Scale deployments across diverse environments (SQL-based workflows, pandas, RAG pipelines, distributed compute). Define evaluation standards: Pass@N, multi-run testing, retriever benchmarking, component diagnostics, and quality gates. Lead client-facing engagements, delivering workshops … LangGraph, tool orchestration). Excellent communication skills with the ability to run workshops and shape technical direction. Preferred Experience with PyTorch, TensorFlow, vector DBs, RAG, and distributed inference. Background in dynamic, high-performance environments (start-ups or technical consultancies). Exposure to regulated industries or complex stakeholder landscapes. Proactive mindset ...

NetMind.ai, we're building the next-generation AI/ML platform powered by a global decentralized GPU infrastructure. Our mission is to deliver the simplest and most accessible generative AI solutions on the market and democratize access to AI technology globally. Our AI services range from inference model … within days (or hours) to support client pitches. AI Stack Integration: Utilize Claude Code Agent, Google Gemini, and OpenAI APIs to implement features like RAG, document analysis, and automated workflows. Full-Stack Lite: Use Python and Streamlit to create clean, interactive, and client-ready user interfaces. Prompt Engineering: Design ...