23 of 23 Permanent Retrieval-Augmented Generation Jobs in West London

solutions for documentation, SDKs, configurations and pipelines to enable rapid deployment of GenAI applications (including Retrieval-Augmented Generation (RAG) pipelines) and agents with planning, memory, and workflow orchestration Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor … secure mission-critical applications Previous experience deploying and managing LLM-model based applications and agents Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Exposure to cloud-native microservices architecture Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented ...

reinforcement learning and LLMs. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG) and agentic AI. Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc). Expertise in data ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

learning operations practices Strong working knowledge of large language models (LLMs), including prompting, fine-tuning, retrieval-augmented generation (RAG), and evaluation techniques, and the ability to apply them to real product challenges Experience with agentic AI frameworks and libraries in Python, such ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 - Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 - AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 - Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 - Machine Learning Project Put your machine learning ...

LLMs and agentic AI. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG) and orchestration of agentic AI systems. Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data, and integrating non-traditional data sources. ...

high-quality production code while guiding technical direction - Deep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques - Proven ability to take complex AI solutions from prototype … pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale - Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration - Make key technical decisions while remaining accountable ...

development, building scalable, resilient, and production-grade systems Hands-on experience developing AI-powered applications, including large language models (LLMs), AI agents, retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization techniques Proven ability to take AI solutions from concept and experimentation through … services that power AI applications, intelligent automation solutions, and AI agents Develop and deploy advanced LLM-powered applications using techniques such as retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization Create robust data and inference pipelines that support both real-time ...

core foundation for their application logic and AI capabilities. Guide startups on implementing advanced AI workloads, including Generative AI, Large Language Models (LLMs), RAG systems, and agentic workflows, utilizing both first-party (Gemini) and partner model ecosystems (e.g., Anthropic). Partner with the Sales team to qualify opportunities, address technical ...

Skills: Proven expertise and hands-on delivery of AI/ML in financial services Strong technical depth in GenAI/LLMs, prompt engineering, RAG architecture, fine-tuning, vector databases Knowledge of evaluation metrics for LLMs and safety/guardrail techniques Understanding of supervised learning and data engineering fundamentals Leadership experience ...

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. ...

launch and architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Active, or the ability to obtain, a Security Check ...

e.g., Google Cloud Platform (GCP)). Experience building pipelines for structured and unstructured data using both vector databases and retrieval augmented generation (RAG) like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Active, or the ability to obtain ...

experience with software development using Python or similar coding languages. Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience taking production-grade AI-driven solutions from conception to launch, and architecting AI systems on cloud platforms (e.g. ...

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 ...

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. ...

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 ...

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 ...