1 to 25 of 42 Permanent Retrieval-Augmented Generation Jobs in the City of London

architecture, engineering, scalability, and deployment. Design and build AI solutions using large language models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI approaches. Remain hands-on with development, contributing to Python code, architecture reviews, and technical problem-solving. Drive best practices across MLOps, testing … development skills with experience across modern machine learning and data science frameworks. Hands-on experience with large language models, generative AI, prompt engineering, and RAG architectures. Experience with Databricks, MLflow, Spark, and cloud-based AI platforms (Azure preferred). Strong understanding of MLOps, software engineering best practices, and production deployment ...

Position Overview We are seeking a Senior Machine Learning Engineer to design, deploy, and optimize our next-generation Conversational AI and Data Analytics platforms. You will bridge the gap between AI research and production engineering. Your primary focus will be optimizing and scaling core Speech … e.g., Kubeflow, MLflow). Preferred Qualifications Conversational Context: Experience with dialogue management, prompt engineering, and Retrieval-Augmented Generation (RAG). Data Analytics: Familiarity with real-time data streaming (e.g., Kafka) and vector databases (e.g., Pinecone, Milvus, Qdrant). Quantization: Experience with model compression techniques ...

reference architectures, POV frameworks, or architectural playbooks — at scale.Fluency across the modern data and AI stack: cloud data platforms (Snowflake, Databricks, BigQuery), agentic frameworks, RAG, vector databases, LLM orchestration, data governance, and enterprise integration patterns.Experience with prompt engineering, agent lifecycle management, and hands-on prototype development.Hands-on proficiency in programming … Redshift.AI & Agentic Architecture Foundational ML concepts, data preparation, Python, applied AI, Generative AI, prompt engineering, retrieval-augmented generation (RAG), vector stores, and agentic architectures. Hands-on familiarity with platforms like Databricks, Snowflake, SageMaker, or Vertex. Agent lifecycle management, observability, and governance frameworks.Agentforce & Salesforce Platform ...

AI. Experience developing AI-enhanced digital assistant solutions such as Microsoft Copilot. Practical experience with Retrieval-Augmented Generation (RAG) architectures and Machine Learning Operations (MLOps). Strong stakeholder engagement skills, with the ability to communicate technical solutions clearly to both technical and non-technical ...

Azure AI Experience building Agentic AI workflows, orchestration frameworks, AI copilots, or autonomous process automation solutions Knowledge of AI-driven APIs, semantic search, RAG architectures, and vector database integrations Azure certifications such as AZ-900, AZ-204, or AI-900 would be advantageous Key Responsibilities Design, develop, and maintain scalable ...

cloud‐native delivery patterns What Will Make You Stand Out Experience building, deploying, and evaluating multi‐agent AI solutions, agent orchestration patterns, RAG architectures, and enterprise integrations Knowledge of agent communication protocols and interoperability patterns, such as MCP and A2A Ability to balance innovation with practical delivery considerations, including risk ...

implementing end-to-end AI/ML solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure ...

with Python and modern AI/ML frameworks such as PyTorch and/or TensorFlow . Deep understanding of LLMs, Generative AI, prompt engineering, RAG architectures and vector databases . Experience with frameworks and tooling such as LangChain, LangGraph or similar open-source AI toolkits . Experience fine-tuning, evaluating ...

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 ...

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 ...

model evaluation, testing, validation, and responsible AI. Design and improve AI systems using techniques such as prompt engineering, retrieval augmented generation (RAG), and AI agents. Mentor data scientists and provide technical leadership through code reviews and coaching. Partner with engineering teams to deliver scalable … What we're looking for Extensive experience developing AI and machine learning solutions in production environments. Strong expertise in large language models, generative AI, RAG, prompt engineering, and agentic AI. Excellent Python programming skills and experience with modern AI and data science frameworks. Strong foundation in statistics, machine learning ...

track record delivering enterprise-scale AI/ML solutions into production Strong experience leading technical teams and complex transformation programmes Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms ...

system design, application development, testing, and operational stability. Experience integrating AI/ML techniques into software systems, including familiarity with LLMs, Generative AI, NLP, RAG, AI evals, and coding assistants. Managing and mentoring software engineering or AI/ML teams, with experience as a hands-on practitioner delivering production-grade ...

Salesforce Financial Services Cloud | Snowflake | ComplyAdvantage | OCS | SQL | Python | REST APIs | Event-Driven Architecture | Cloud | CI/CD | DevSecOps | AI/ML | GenAI | LLMs | RAG | Data Governance | Data Lineage If you have the above experience please apply immediately ...

repeat manual work. Secure AI Application and Cloud-AI Guardrails Define secure design patterns for AI-enabled applications, including LLM-based features, retrieval-augmented generation, AI agents, AI APIs, copilots, and automation workflows. Establish cloud security requirements for AI workloads, including identity, secrets, data … NIST AI Risk Management Framework, NIST Generative AI Profile, OWASP Top 10 for LLM Applications, or Cloud Security Alliance AI security guidance. Experience with RAG architecture, AI agents, vector databases, AI APIs, prompt engineering, or AI application threat modelling. Experience building security knowledge assistants, prompt libraries, AI-assisted review workflows ...

deliver measurable value. Lead discovery sessions, solution design and technical workshops with senior stakeholders. Design pragmatic AI solutions across Generative AI, Agentic AI, LLMs, RAG and modern cloud platforms. Provide architectural guidance and technical leadership throughout delivery programmes. Remain hands-on where required, supporting engineering teams on complex engagements. Work … before moving into AI. Experience designing enterprise AI solutions using technologies such as: Generative AI Large Language Models (LLMs) Retrieval Augmented Generation (RAG) Agentic AI Cloud AI Services (Azure, AWS or Google Cloud) Comfortable engaging with both technical and non-technical stakeholders. Experience supporting ...

analytical reasoning. Exceptional communication and collaboration skills. Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX. Experience with Large Language Models, including RAG and fine-tuning techniques. Familiarity with compute infrastructure necessary to support operating AI and ML technology. For more information about DRW's processing activities ...

wider organisation. About the role: This position serves as a subject matter expert for Machine Learning Engineering, supporting production AI/ML, LLM/RAG, and agentic workflow capabilities for legal content products. In addition to writing code on complex systems, this position provides technical direction on architecture, MLOps, responsible … including model lifecycle management, CI/CD, testing, monitoring, release management, observability, and operational support. Practical experience with LLM-based capabilities, including retrieval-augmented generation, semantic search, embeddings, prompt design, evaluation, guardrails, and observability. Experience with agentic workflows, tool orchestration, and multi-step ...

research and make investment decisions. Working closely with Portfolio Managers, Research Analysts, Sustainability teams, Architects and Engineers, you will define and deliver next-generation capabilities leveraging Generative AI, agentic workflows and advanced analytics to create measurable business value across global investment teams. Key Responsibilities Own the vision, roadmap … investment data, holdings, benchmarks and fund look-through capabilities. Experience delivering AI-powered solutions, including Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI assistants, agentic workflows and knowledge discovery platforms. Demonstrated product management experience, including product strategy, roadmap development, prioritisation, backlog management ...

experience Strong React.js, Node.js and TypeScript experience Next.js and RESTful APIs GCP including Cloud Run Kubernetes and Terraform AI/LLM integrations, AI agents, RAG or agentic workflows Unit, integration and end-to-end testing CI/CD, secure coding and DevSecOps Experience building scalable, high-traffic applications Strong ...

work forward independently. What makes you stand out? Experience building AI/LLM-enabled products in production or controlled enterprise environments (e.g. agentic workflows, RAG, prompt engineering, evaluation and governance patterns) Experience with React/Next.js and modern web tooling. Familiarity with document/NoSQL stores (e.g. MongoDB) and data ...

concept work. Reviewing code and technical outputs to maintain high engineering and quality standards. Designing and delivering Generative AI and LLM solutions , including RAG architectures, prompt engineering, vector search and integration with Azure AI services. Defining engineering approaches for LLM applications, agentic AI systems, machine learning solutions and AI platforms … TensorFlow . Practical experience with Databricks , including MLflow and Spark-based data processing. Hands-on knowledge of Generative AI and LLMs , including prompt engineering, RAG architectures and vector search. Strong understanding of MLOps , including CI/CD, model testing, deployment, monitoring and model lifecycle management. Cloud experience, ideally within ...

/GCP). Ability to standardise and influence across teams. Nice to Have Lakeflow connectors, RBAC/masking, GenAI (Mosaic AI, Vector Search, RAG), Lakebase. #J-18808-Ljbffr ...

such as Microsoft, Oracle, or similar platforms.Background in change management, organizational design, or enterprise transformationExperience with AI/ML concepts beyond LLMs, including NLP, RAG architectures, and model evaluation frameworksA get-things-done mindset with strong bias for action — comfortable operating in unstructured fast moving environmentsUnleash Your PotentialWhen you join ...

experience driving cloud/AI transformation within Insurance, Financial Services, or similarly highly regulated industries. Technical Acumen: A strong architectural understanding of GenAI concepts (RAG, AI Agents, Agentic Workflows) and DevSecOps automation. Delivery Mastery: Expertise in benefits management, project planning, and crisis mitigation for large-scale enterprise deployments. To Apply ...