26 to 50 of 51 Retrieval-Augmented Generation Jobs in the South West

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

across a range of AI and cloud projects. Responsibilities will include: Designing and delivering Generative AI and Machine Learning solutions Building applications using LLMs, RAG frameworks and AI orchestration tools Working directly with clients to understand business challenges and define AI-driven solutions Leading architecture and engineering decisions across Azure … experience building AI-powered applications and deploying them into production Software Engineering or Product Engineering background Strong Python development skills Experience working with LLMs, RAG architectures and modern AI frameworks Multi-cloud experience across Azure, AWS and GCP Strong understanding of cloud-native architectures and scalable application design Experience with ...

complex datasets, including time series data, from various sources (web APIs, databases, real-time streams). Leverage Generative AI platforms and frameworks agents, RAG, prompt and context engineering, evaluations and AI SDLC to deliver novel capabilities for the trading organisation. Tap into expertise in AWS cloud services (S3, Redshift … Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. Mastery of SQL (including advanced optimisation techniques) and experience with relational databases (PostgreSQL preferred), including data modelling and design skills. ...

build the right thing, not just a technically impressive thing. Technical foundations that match your level: For senior hires, your toolkit includes Python, RAG, API integrations, and agent architecture. For mid-level hires, your learning trajectory and intellectual curiosity matter as much as your current depth. Communication that bridges ...

outcomes. Even better... Experience building or deploying AI/LLM agents in production hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) working closely with technical counterparts. You've been a founder, founding team member, or operator you know how to balance craft, ownership ...

outcomes. Even better... Experience building or deploying AI/LLM agents in production hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) working closely with technical counterparts. You've been a founder, founding team member, or operator you know how to balance craft, ownership ...

outcomes. Even better... Experience building or deploying AI/LLM agents in production hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) working closely with technical counterparts. You've been a founder, founding team member, or operator you know how to balance craft, ownership ...

agentic AI solutions. Strong understanding of Azure AI architecture, security, governance and best practice. Experience connecting internal/proprietary business data to LLMs, including RAG, grounding, model customisation and/or fine-tuning. The ability to operate as both a hands-on technical SME and trusted advisor. Previous experience training ...

improve Design and ship multi-agent systems and production-grade automations that measurably improve how internal teams and customer-facing staff work Build RAG pipelines for internal knowledge retrieval that ground agents in real organisational context Keep the AI tooling stack healthy as usage scales across 2,500+ … development Hands-on experience building multi-agent systems using agentic frameworks — LangChain, LangGraph, MCP, Google ADK or similar Experience with RAG pipelines — retrieval-augmented generation for internal knowledge and workflow automation Background in enterprise tooling — rapid prototyping tools (Vercel/Railway), identity automation (Entra ...

with agentic coding tools (Claude Code, Gemini CLI, Codex): a working demo, an automated analysis, a small internal tool. Apply core GenAI concepts — prompting, RAG, agents, context engineering — well enough to explain them to clients and stress‐test vendor claims. Develop specialization in at least one AI platform ecosystem: Google … business, technology, or another field related to our work. Preferred Experience Strategy consulting and/or digital marketing knowledge. Familiarity with GenAI concepts: RAG, agents, prompting, context engineering. Exposure to a major AI or cloud platform (Google, Anthropic, OpenAI; GCP, Azure, AWS). Experience contributing to proposals or thought leadership. ...

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 ...

software development. The ideal candidate will be proficient in Python and have hands-on experience with Generative AI and Retrieval Augmented Generation solutions, particularly in the context of software testing. This role requires a blend of technical expertise, innovative thinking, and effective communication skills … quality assurance solutions. Responsibilities: Develop and implement AIML solutions focused on enhancing software testing processes. Utilize Generative AI and Retrieval Augmented Generation techniques to improve testing efficiency and accuracy. Work with Large Language Models (e.g., GPT, Claude) to create and optimize AIML applications. Leverage ...

Tech Lead level, with the ability to be both highly technical and an effective people manager Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval … About the Team Our AI Strategy and Innovation team shapes Moody's product ecosystem through AI, data, and strategic partnerships to deliver next-generation solutions. The team embeds AI across product strategy using large language models, agentic platforms, and advanced analytics to enhance decision-making and client outcomes. ...

mainly Python across the modern AI engineering stack - harness engineering, skills and tool building, agent workflows and orchestration, agent hosting and sandboxing, guardrails, evals, RAG and context engineering, and tokenomics (cost, latency, model selection). Production-grade LLM system experience is the core requirement. You will work on three types … your primary language. LLM-powered systems in production: real-world experience working with models via APIs - harnesses, orchestration, structured output, tool use and agents, RAG where appropriate. Evals and quality: designing evaluation sets, measuring accuracy, recall and precision for LLM steps, regression-testing prompts and workflows. Safety and guardrails ...

scalable application programming interfaces, microservices, and distributed systems Practical experience building enterprise AI applications using large language models, including agents, retrieval augmented generation, orchestration frameworks, and model optimization Demonstrated ability to own services, components, or features end to end, from technical design through production … from technical design through deployment, monitoring, production support, and continuous improvement Build and enhance large language model application features using retrieval augmented generation, orchestration frameworks, evaluation methods, agentic workflows, and tool integration Contribute to technical designs, participate in design reviews, and identify risks, constraints ...

teams to understand business and technical challenges. Design and develop AI-powered prototypes, proof-of-concepts and product solutions . Apply Generative AI, LLMs, RAG and prompt engineering to real-world use cases. Evaluate and integrate AI platforms, tools, APIs and cloud technologies. Contribute across the full product engineering lifecycle … experience across AI, software development and product engineering . Strong proficiency in Python and JavaScript . Hands-on experience with Generative AI, LLMs and RAG architectures . Experience with prompt engineering and AI APIs/integrations. Experience building prototypes, proof-of-concepts or production-ready solutions. Strong understanding of modern ...

challenge design decisions, and assess technical risk Deep expertise in enterprise AI applications built on large language models, including agents, retrieval augmented generation, orchestration frameworks, model optimization, and evaluation frameworks Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses … delivery outcomes across the portfolio Drive architectural decisions, organizational alignment, and integration of AI-powered solutions using large language models, retrieval augmented generation, orchestration frameworks, and agentic workflows Establish engineering excellence through architecture reviews, code reviews, automated testing, observability, security standards, operational excellence ...

Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain. We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. … expertise in CPG, retail, financial services, healthcare, or telecom. Experience taking clients from AI experimentation to scaled, governed adoption. Familiarity with context engineering concepts: RAG, semantic layers, knowledge bases, MCP. An existing network and reputation in the US data & AI market. Why you should join us We are united ...

Integrate agents and applications with existing client platforms using Microsoft Graph, REST APIs and Azure services Design solutions involving knowledge retrieval, RAG, document processing and autonomous workflows Advise clients on AI security, governance, identity and deployment considerations Contribute to technical documentation, development standards and solution architecture Work across … Platform , particularly Power Automate and Power Apps Microsoft 365 Copilot and the wider M365 ecosystem Microsoft Foundry/Azure AI services Azure AI Search, RAG and generative AI solutions Conversational AI, agentic AI and autonomous workflows Microsoft Graph and REST API integrations Dataverse, SharePoint and Teams Entra ID, app registrations ...

leadership across a multidisciplinary AI engineering team Shape the architecture and technical direction for AI across the product suite Lead the delivery of LLM, RAG and agentic AI solutions Take ideas from discovery and proof of concept through to production Establish standards for evaluation, security, observability, governance and cost control … ability to lead others, make architectural decisions and communicate technical trade-offs clearly to non-technical stakeholders. Experience with Azure OpenAI, Azure AI Search, RAG, agentic workflows, Semantic Kernel or Microsoft Agent Framework, vector databases, evaluation frameworks and responsible AI controls would be particularly useful. Salary and benefits ...

hackajob is partnering directly with Google to hire for this role. Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond … continue to push technology forward. AI in the Gemini Era is data-centric: the quality of the data used for training, fine-tuning, or RAG, matters more to the performance of the end product than almost anything else. Our mission is to improve the quality of models that Google releases ...