9 of 9 Remote/Hybrid Retrieval-Augmented Generation Jobs in Scotland

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents.* Scale existing POCs to production-ready solutions for customer use.* Design and develop FullStack applications for both GenAI and non-GenAI projects. ...

architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps … business teams to deliver end-to-end solutions. Tech environmentPython, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure. What we're looking forProven enterprise AI or ML architecture design, strong cloud and modern data ...

multi‐modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval‐Augmented Generation (RAG), APIs, and enterprise data integrations Fine‐tune, optimize, and deploy large language and multi‐modal models with a focus on scalability … within agile delivery environments Bonus Points For Experience building AI agent frameworks or autonomous orchestration platforms Knowledge of vector databases, semantic search, and advanced RAG architectures Experience with cloud platforms such as AWS, Azure, or GCP for AI workloads Familiarity with financial services, banking, or regulated enterprise environments Exposure ...

scale in production environments and create capacity for our business partners. From AI-powered investment insights and risk management solutions to next-generation agentic workflows - our work is helping to shape the future of BlackRock. Our teams work on some of the firm's highest priority strategic initiatives … standards such as Model Context Protocol (MCP) for connecting agents to tools and data. Experience with retrieval systems for agents: retrieval-augmented generation, embedding models, vector databases, and long-term memory. Experience with machine learning libraries (e.g. PyTorch, Tensorflow), cloud platforms ...

scale in production environments and create capacity for our business partners. From AI-powered investment insights and risk management solutions to next-generation agentic workflows - our work is helping to shape the future of BlackRock. Our teams work on some of the firm's highest priority strategic initiatives … standards such as Model Context Protocol (MCP) for connecting agents to tools and data. Experience with retrieval systems for agents: retrieval-augmented generation, embedding models, vector databases, and long-term memory. Experience with machine learning libraries (e.g. PyTorch, Tensorflow), cloud platforms ...

scale in production environments and create capacity for our business partners. From AI-powered investment insights and risk management solutions to next-generation agentic workflows - our work is helping to shape the future of BlackRock. Our teams work on some of the firm's highest priority strategic initiatives … standards such as Model Context Protocol (MCP) for connecting agents to tools and data. Experience with retrieval systems for agents: retrieval-augmented generation, embedding models, vector databases, and long-term memory. Experience with machine learning libraries (e.g. PyTorch, Tensorflow), cloud platforms ...

prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting … collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma ...

Experience designing and operating APIs, microservices, distributed systems, and event-driven architectures at enterprise scale. Exposure to Generative AI, large language models, retrieval-augmented generation, semantic search, embeddings, knowledge retrieval, or agentic workflow patterns. Strong focus on software quality, including automated testing ...

advisor to client CxOs. Key Responsibilities Architecture and Solution Design: Architect enterprise AI solutions using frontier models (Claude, GPT, Gemini family) across agentic automation, RAG, copilots, and multi-modal applications. Pre-Sales and Discovery: Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architectures … specifically on applied AI/ML or Generative AI. Hands-on GenAI Depth: Proven experience architecting solutions with frontier modelsincluding prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design. LLMOps/MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment ...