51 to 75 of 2,239 LLM Jobs in London

track record of taking AI prototypes to production in enterprise environments.Education: BS in Engineering, Computer Science or equivalent; 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 ...

Systems, or a related field, or equivalent practical experience. Machine Learning: Expertise in time-series forecasting, clustering, and correlation algorithms. Generative AI: Experience with LLM prompting, Retrieval-Augmented Generation (RAG), and LangChain. Cloud Infrastructure: Deep understanding of AWS, Azure, or GCP infrastructure componentsAdditional Preferred Qualifications: Experience with enterprise observability ...

Description AI Large Language Model (LLM) Technology Architect Career Level: Associate Manager/Specialist Location: London YOU ARE As a hands-on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands … cloud vendor. Practical experience in the Agentic,LLMand Generative AI space. Well versed in coding using python Solid foundation in architecting and operationalizing LLM driven application architecture patterns. Professional working experience in coding engineering, machine learning, deep learning and NLP solutions and applications. Several years of hands on experience ...

strategic AI platform partnerships (e.g., Google, Anthropic), third‐party tooling, and outsourced delivery models Qualifications 15+ years of experience in Technology – Required: Generative AI & LLM Engineering: Deep, hands‐on expertise in large language models including model selection, fine‐tuning, prompt engineering, retrieval‐augmented generation (RAG), vector database design, and evaluation ...

strategic AI platform partnerships (e.g., Google, Anthropic), third-party tooling, and outsourced delivery models## **Qualifications:****15+ years of experience in Technology - Required:*** Generative AI & LLM Engineering: Deep, hands-on expertise in large language models including model selection, fine-tuning, prompt engineering, retrieval-augmented generation (RAG), vector database design, and evaluation ...

including strategic AI platform partnerships (e.g., Google, Anthropic), third-party tooling, and outsourced delivery modelsQualifications:15+ years of experience in Technology - Required: Generative AI & LLM Engineering: Deep, hands-on expertise in large language models including model selection, fine-tuning, prompt engineering, retrieval-augmented generation (RAG), vector database design, and evaluation ...

ReqID:FEQ327R501Location: LondonSkills: Data Science, Machine Learning, AI, LLM, GenAIMissionAs a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise and strategic customers in architecting ...

agile environmentsBonus Points ForExperience with agentic frameworks (e.g., LangChain, LlamaIndex)Experience in deep learning frameworks and front-end developmentFamiliarity with Langfuse, Langsmith, or other LLM observability toolsUnderstanding of Model Context Protocol and bias/hallucination mitigation techniquesPrevious success in integrating GenAI solutions into enterprise-scale systemsWhy Join CapcoDeliver high-impact ...

STEM discipline, or equivalent professional experience.Strong experience developing AI solutions using Python and modern AI frameworks such as LangChain or similar technologies.Deep understanding of LLM architectures, Generative AI, Agentic AI concepts, RAG frameworks, embeddings, and prompt engineering.Experience designing and deploying solutions on Azure, AWS, or GCP cloud platforms.Experience working ...

equivalent professional experience. Strong experience developing AI solutions using Python and modern AI frameworks such as LangChain or similar technologies. Deep understanding of LLM architectures, Generative AI, Agentic AI concepts, RAG frameworks, embeddings, and prompt engineering. Experience designing and deploying solutions on Azure, AWS, or GCP cloud platforms. Experience working ...

engineering domains. End‐to‐end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments. Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine‐tuning LLMs for domain‐specific enterprise applications. Strong expertise in MLOps and LLMOps, ensuring scalable ...

engineering domains. End-to‐end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments. Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine‐tuning LLMs for domain‐specific enterprise applications. Strong expertise in MLOps and LLMOps, ensuring scalable ...

relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps) Experience working on AIML systems and/or prior experience collaborating with data scientists J.P. Morgan is a global leader in financial ...

optimize retrieval, and drive data‐driven decision‐making; conduct A/B tests and performance evaluations. Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices. Required Qualifications, Capabilities, and Skills: Advanced degree in Computer Science, Data Science, Machine Learning, or related field. Experience building ...

optimize retrieval, and drive data-driven decision-making; conduct A/B tests and performance evaluations. Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices. Required Qualifications, Capabilities, and Skills Advanced degree in Computer Science, Data Science, Machine Learning, or related field. Experience building ...

production. High proficiency in at least one modern language: Python, JavaScript/TypeScript, Java, or Apex. Hands‐on AI & Grounding Expertise: Deep experience with LLM orchestration, prompt tuning, and building RAG pipelines, vector search indexes, and knowledge base retrievers for enterprise data. Multi‐Agent Systems & API Mastery: Practical experience with ...

with multiple modern programming languages including Python, Golang, TypeScript and similar technologies in an AWS/Cloud environment Experience in the use of GPT, LLM, RAG, Gen AI, Prompt Engineering related technologies Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming ...

optimize retrieval, and drive data-driven decision-making; conduct A/B tests and performance evaluations. Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices. Required Qualifications, Capabilities, and Skills: Advanced degree in Computer Science, Data Science, Machine Learning, or related field. Experience building ...

hybrid search, document ingestion, tool/function calling, Model Context Protocol (MCP), and agent orchestration AI Evaluation & Quality: Eval harnesses and golden datasets, LLM-as-judge and human-in-the-loop review, regression suites, and red-teaming Observability & Monitoring: Prometheus, Grafana, Datadog, Splunk, Elastic/ELK, OpenTelemetry, including GenAI tracing ...

from discovery through to adoption.Experience collaborating around BI/analytics tools (Power BI, Tableau, etc.)Exposure to AI platforms (e.g. Azure OpenAI/other LLM services, data science environments, MLOps platforms) – as a partner/user rather than a builderAdditional InfoHybrid working: The places that you work from ...

systems Go beyond adopting AI tools - define how intelligent systems become structural, load-bearing parts of the platforms your teams own. Whether that's LLM-powered workflows, ML models embedded in analytical processes, agentic automation, or AI-augmented developer tooling, bring the depth to evaluate, architect, and champion these capabilities ...

maintain production-grade ML orchestration pipelines using tools such as Dagster, Airflow, Prefect, or similar technologies. Deploy, monitor, and scale machine learning models and LLM-powered solutions in production environments. Build and maintain cloud-native infrastructure using Kubernetes and Infrastructure as Code technologies such as Terraform or Bicep. Develop robust ...

engineering experience with Python, APIs, microservices, debugging, and code reviewProven experience building and deploying Generative AI or Agentic AI applications in productionDeep understanding of LLM concepts, RAG patterns, prompt design, and evaluation methodologiesExperience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel)Familiarity with orchestration strategies like planner/ ...

technology and transformation. Solid hands-on technical skills – for example SQL and Python, data manipulation and engineering, and exposure to generative AI/LLM tools, machine learning or analytics platforms such as Power BI or Alteryx. Experience with using low code applications such as Microsoft Copilot Studio and Power Platform. ...

working on: Designing and deploying production-grade agentic and multi-agent systems Building RAG pipelines, including embeddings, chunking, vector search and context engineering Integrating LLM APIs across providers such as OpenAI, Anthropic, Vertex AI and open-source models Building orchestration, tool invocation, routing and memory capabilities Developing evaluation frameworks ...