1 to 25 of 667 Remote/Hybrid LLM Jobs in London

grade Generative AI applications, including:* Retrieval-Augmented Generation (RAG)* AI Agents and Agentic Workflows* Prompt Engineering and Prompt Optimization* Model Evaluation and Observability Frameworks* LLM Fine-tuning and Adaptation Techniques* Hands-on experience with Azure AI Foundry, Azure OpenAI Service, Model Context Protocol (MCP), and modern AI orchestration frameworks.* Strong ...

tool-calling frameworks (e.g. LangGraph or equivalent), including familiarity with the Model Context Protocol (MCP)• Evaluation engineering (golden datasets, regression gates in CI, LLM-judge calibration)• Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust)MLOps & LLMOps• Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker ...

agentic AI systems—tool use, orchestration, multi‐step reasoning, or agent frameworks (e.g. LangGraph, LangChain, CrewAI, AutoGen, or similar). Experience with GenAI/LLM systems in a production context (RAG, prompt orchestration, evaluation, guardrails, cost/latency optimisation). Exposure to MCP (Model Context Protocol) and tool‐based/ ...

Hugging Face, OpenAI APIs etc)Experience in building and optimising systems for performance, scalability, and reliability Understanding of ML fundamentals (training, evaluation, deployment) and LLM-specific challenges (prompt engineering, latency, cost optimisation, hallucinations, evaluation) Experience with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (Terraform etc). Hands ...

RBAC and Cost Controls.Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens.Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK.WHAT YOU'LL LOVE ABOUT WORKING HEREWe ...

know yet). You’ll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It’s all live lectures, tutor-led group work and real-world challenges from ...

Generative AI solutions in production environments. Demonstrable experience successfully designing and launching multiple enterprise GenAI implementations beyond proof-of-concept stage. Strong expertise in LLM ecosystems including OpenAI, Anthropic, Gemini, and related model platforms. Hands-on experience with RAG architectures, Agentic AI frameworks, and orchestration tools such as LangChain, LangGraph ...

Generative AI use cases. Design and build APIs and microservices that integrate AI capabilities into internal and external workflows. Develop, fine‐tune, and deploy LLM‐based applications (e.g., chatbots, assistants, knowledge extraction tools). Architect scalable AI infrastructure on cloud platforms (AWS, GCP, or Azure), leveraging containerisation and IaC. Implement ...

Generative AI use cases. Design and build APIs and microservices that integrate AI capabilities into internal and external workflows. Develop, fine-tune, and deploy LLM-based applications (e.g., chatbots, assistants, knowledge extraction tools).Architect scalable AI infrastructure on cloud platforms (AWS, GCP, or Azure), leveraging containerisation and IaC.Implement CI/ ...

Hugging Face, OpenAI APIs etc) Experience in building and optimising systems for performance, scalability, and reliability Understanding of ML fundamentals (training, evaluation, deployment) and LLM‐specific challenges (prompt engineering, latency, cost optimisation, hallucinations, evaluation) Experience with cloud platforms (AWS, GCP, Azure) and infrastructure‐as‐code (Terraform etc). Hands ...

advanced analyticsCloud & Data Platforms – Microsoft Fabric, Databricks, Snowflake, Azure, AWS and GCPAI Technologies – GenAI frameworks, Agentic AI, vector databases, semantic search, knowledge retrieval and LLM application developmentData & Visualisation – Power BI, Tableau, Looker and other business intelligence toolsConsulting, Communication & Leadership:Ability to work effectively with both business and technical stakeholders.Strong communication ...

Senior AI Engineer/AI Engineering Consultant/Generative AI Consultant/Senior Machine Learning Engineer/AI & ML Consultant/MLOps Engineer/LLM Engineer/AI Engineering Consultant/Senior AI Engineer/Generative AI Engineer/AI Solutions Architect/Data & AI Consultant/AI Solutions Consultant ...

Senior AI Engineer/AI Engineering Consultant/Generative AI Consultant/Senior Machine Learning Engineer/AI & ML Consultant/MLOps Engineer/LLM Engineer/AI Engineering Consultant/Senior AI Engineer/Generative AI Engineer/AI Solutions Architect/Data & AI Consultant/AI Solutions Consultant ...

other relevant enterprise platforms. Understand the foundations required for safe and scalable AI delivery, including identity, permissions, environments, data lineage, observability, evaluation, auditability, LLM access patterns and responsible AI controls. Work closely with Data Solutions & Architecture colleagues to ensure AI use cases are built on the right data foundations. Understand ...

part of a broader project team, remotely or face to face, and confident challenging established approaches. Desirable Experience: Experience running AI/LLM solutions in production at scale, including evaluation frameworks, guardrails and cost management. Experience designing or orchestrating multi-agent workflows, and familiarity with agent protocols (e.g. ...

Agentic AI systems into production environments Expertise in Python engineering for APIs, microservices, testing and CI/CD workflows Strong working knowledge of LLM capabilities, including prompt design, structured outputs, tool calling and retrieval strategies Hands-on experience with agent orchestration frameworks (LangGraph, AutoGen, CrewAI or Semantic Kernel) Proven experience ...

DevOps: Experience with Kubeflow, Docker, Kubernetes, and Linux environments. CI/CD: Proficiency in building and managing continuous integration and deployment pipelines. GenAI/LLM: Experience with LLMs, GenAI APIs, Model Garden, and GenAI Studio. Good to Have Experience with AlloyDB and enterprise database solutions. Familiarity with PaLM embeddings ...

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 ...

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 ...

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/ ...

commitment to clean coding standards (SOLID/DRY), modular design, and comprehensive unit/integration testing. Generative AI Deep Dive: Hands-on experience with LLM training cycles, parameter-efficient fine-tuning (PEFT), and sophisticated prompt engineering. Inference Stack: Experience with high-performance inference servers (e.g., vLLM, TGI, or Triton ...

years in software, data, or platform engineering, with a track record of shipping and operating production systems rather than prototypes. Production experience with LLM applications and agentic systems, covering prompt and context engineering, agent development, retrieval, tool use, evaluation, and deployment at scale. Strong Python and SQL, with the judgement ...