126 to 150 of 501 Retrieval-Augmented Generation Jobs in London

advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context‐window management and production guardrails; MCP, tool‐augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance and residency practices. Cloud ...

advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context-window management and production guardrails; MCP, tool-augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance and residency practices. Cloud ...

learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling, RAG, agents, prompt engineering, or agentic patterns for enterprise workflows. Production ML/LLMOps: Experience with model deployment, monitoring, MLOps/LLMOps, and lifecycle management across ...

/inference optimization, MLOps lifecycle management, and integration with cloud-native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool‐calling, multi‐agent orchestration, and guardrails), AI observability, and natural language querying of structured data. Provide advanced technical support ...

backend API services, model integration, model monitoring, evaluations and deployments Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering, RAG implementation Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language Implement evaluation frameworks to measure and improve GenAI feature ...

experience designing or delivering AI, data, analytics, ML, GenAI, agentic AI, or automation solutions.1+ year of hands-on or solutioning experience with GenAI, LLMs, RAG, AI agents, or enterprise AI platforms. Experience producing solution blueprints, work estimates, delivery plans, staffing models, assumptions, dependencies, SOW inputs, and pricing or commercial inputs. ...

Practical experience implementing components of data pipelines, including real-time streaming tools (AWS Kinesis, Kafka), data orchestration (dbt, Airflow), and managing vector databases for RAG architectures. Observability & Cost Management: SRE/Platform experience with the practical application of real-time monitoring and cloud cost optimisation using native CSP tools ...

Generative AI. Demonstrated ability to architect end‐to‐end Data & AI solutions, with specific expertise in modern Generative AI concepts (e.g., fine‐tuning, RAG, MLOps for LLMs), using either open source and/or ISV tools such as Dataiku, Domino, DataRobot etc. Strong proficiency in a core programming language (e.g. ...

backend API services, model integration, model monitoring, evaluations and deployments Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering, RAG implementation Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language Implement evaluation frameworks to measure and improve GenAI feature ...

architecture for unstructured document ingestion, reasoning, and output generation Design LLM-centric and hybrid AI architectures combining: OCR RAG systems Agentic workflows Design and govern prompt strategies and prompt frameworks for: Loss run and insurance document extraction & normalization Claims summarization, triage, and fraud signal generation Underwriting … platforms Experience integrating AI solutions into enterprise systems .NET (Backend) and React (Frontend) Developer Prompt Engineering & LLM Design Retrieval Augmented Generation (RAG) Architectures Skills and Personal attributes we would like to have: OCR systems for document ingestion and classification AI Governance & Token Economics ...

infrastructure required to run AI workloads reliably, moving client architectures from static data lakes to dynamic Vector Databases and Retrieval‐Augmented Generation (RAG) architectures. Agentic Development: Build production‐grade Agentic Workflows and custom AI agents, utilising advanced toolsets to bridge the widening market implementation … maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability tooling (OpenTelemetry) alongside automated cost‐control systems (such as Karpenter, Infracost, OpenCost, or Cloud Custodian). Domain & Sector Experience ...

Python and experience with AI/ML libraries. Familiarity with cloud infrastructure (AWS preferred) for deploying AI systems. Understanding of RAG (Retrieval-Augmented Generation), vector databases, and memory systems. Experience with RPA or automation tooling is desirable. Knowledge of responsible AI principles ...

teams to translate analytical requirements into efficient, production‐grade data solutions. AI‐Ready Infrastructure Design and maintain pipelines supporting Retrieval‐Augmented Generation (RAG) and Context EngineTM workflows. Build high-performance APIs and caching strategies enabling low‐latency data access for AI agents and orchestration ...

technical audiences. Experience gathering and synthesizing requirements across multiple stakeholder groups and influencing product or platform roadmaps. Familiarity with LLM ecosystems (e.g., prompting, RAG, agents, MCP, fine‐tuning, evaluation) and major AI platforms/APIs. Experience in financial services, asset management, or portfolio analytics is a strong plus. Good ...

preferred), Docker/Kubernetes, CI/CD, and monitoring Strong debugging, collaboration, and continuous-learning mindset Nice to Have: Experience with vector databases and RAG (e.g., OpenSearch, ElasticSearch) Ready to build what's next? Oscar Associates (UK) Limited is acting as an Employment Agency in relation to this vacancy. ...

Snowflake, Databricks, BigQuery or equivalent. Strong understanding of Python and SQL environments. Experience delivering Machine Learning models into production. Knowledge of Generative AI, LLMs, RAG and emerging AI technologies. Understanding of MLOps, model deployment, monitoring and lifecycle management. Experience with modern BI and analytics platforms such as Power BI, Tableau ...

audiences. Strong stakeholder management and presentation skills. Technical Skills Python, SQL, and modern data science toolsets. Machine Learning and Predictive Analytics. Generative AI, LLMs, RAG, and Agentic AI frameworks. Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Databricks, or equivalent cloud platforms. Data visualisation and storytelling tools such as Power ...

influencing and communicating with stakeholders across technical and non-technical teamsIdeally, exposure to cloud infrastructure, NLP or large language models (such as fine-tuning, RAG or agents), graph technologies, or experience in the transport sector or with geographic information systems (GIS)More information: Enjoy fantastic perks like private healthcare & dental ...

communicating with stakeholders across technical and non-technical teams Ideally, exposure to cloud infrastructure, NLP or large language models (such as fine-tuning, RAG or agents), graph technologies, or experience in the transport sector or with geographic information systems (GIS) More information: Enjoy fantastic perks like private healthcare & dental insurance ...

production LLM workflows, including prompt/skill design, evaluation, cost control, provider routing, agentic/human‐in‐the‐loop orchestration, embeddings, vector search and RAG Implementation of foundational ML algorithms, classic NLP techniques and LLMs Strong SQL for analytical and production use, ideally PostgreSQL, including complex joins, CTEs and aggregation ...

judgement around data access, PII handling, RBAC, and the security implications of letting AI systems act autonomously. Preferred experience Familiarity with agentic patterns (MCP, RAG, evaluation frameworks) and the maturity to know when a simpler approach beats a more sophisticated one. Experience in a scale-up, SaaS, or other fast ...

using frameworks such as LangGraph and related orchestration tools. Apply modern techniques in:NLPGenerative AIEmbeddings and semantic representationsRetrieval-augmented generation (RAG)AI reasoning and workflow orchestration Evaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption. Contribute to prompt engineering, grounding strategies … context management, and hallucination mitigation efforts. Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows. Search, Retrieval & RAG Systems Design, develop, and optimize search and retrieval pipelines , including lexical, vector, and hybrid retrieval approaches. Contribute to the development and enhancement ...

understand what makes agents perform well in production and how to systematically improve quality through observability and evaluation. Experience with voice AI platforms, RAG systems, and LLM orchestration frameworks is highly desirable. You bring exceptional communication skills, customer empathy, and the drive to build AI solutions that transform enterprise operations … integration Proficiency in Python (production-grade, async programming, type hints) and JavaScript/TypeScript (full-stack development) RAG implementation experience built retrieval-augmented generation systems with vector databases MLOps & deployment hands-on with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code Cloud ...

systems Driving adoption of Agentic AI across multiple engineering teams Defining reusable engineering standards, architectures and implementation patterns Designing and evolving production RAG and retrieval architectures Establishing effective LangGraph/LangChain patterns for agentic applications Improving AI evaluation, testing, observability and production monitoring Developing guardrails, controls and approaches … Python and strong software engineering fundamentals Production Machine Learning/AI engineering AWS Agentic AI and LLM-based applications Retrieval Augmented Generation (RAG) LangChain and/or LangGraph Vector databases and retrieval MLOps and production deployment AI evaluation, testing and observability ...

data, platform, or AI/ML products Preferred: Familiarity with adjacent technologies such as vector databases, semantic search, large language model and retrieval-augmented generation architectures, data catalogs, and lineage tools Deep expertise in artificial intelligence, with a track record of implementing advanced … foundational data infrastructure that unifies and contextualizes information across the organization, powering analytics, search, and next-generation GenAI and retrieval-augmented generation applications. By joining our team, you will be part of exciting work which strives to leverage data, technology ...