126 to 150 of 2,799 LLM Jobs in England

will include up‐skilling people at Accenture and our clients with AI centric engineering. Maintain cutting‐edge expertise — Stay ahead of the curve on LLM capabilities, with a focus on the SDLC, agentic frameworks, evaluation methodologies, and the AI product development ecosystem. Build strong relationships — Develop trusted working relationships with ...

Experience with AI observability, evaluation frameworks assessing quality, latency, cost, and reliability, and implementing enterprise-grade security guardrails and responsible AI practices for large language model applications Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience adhering ...

queues. Hands-on experience building and deploying AI applications in production environments. Experience implementing RAG pipelines , AI agent orchestration , and performance monitoring. Familiarity with LLM evaluation techniques and tools for measuring model accuracy, reliability, and safety. What We Offer: You will be reporting directly to the founders, who have ...

processing frameworks Systems-Level Programming: Experience with low-level systems programming such as storage systems, Kubernetes operators, OS-level software development, or daemon services (llm-d, system agents) ML Platform Engineering: Experience productionizing ML pipelines, batch job orchestration, model fine-tuning workflows, and Jupyter notebook orchestration systems Enterprise Deployment: Experience ...

Python development skills. Experience integrating and consuming REST APIs. Hands-on experience with Docker and Kubernetes. Knowledge of vector databases, embeddings, RAG architectures, and LLM orchestration frameworks. Experience with cloud technologies, networking, identity and access management, and security controls. Experience integrating AI solutions with Microsoft 365 technologies, collaboration platforms ...

Experience with Databricks model training and inference workflows Databricks Apps and Lakebase Experience with RAG pipelines Experience with vector databases (Weaviate, Milvus) Familiarity with LLM evaluation frameworks (e.g. DeepEval) Soft Skills Strong sense of ownership and accountability Strong stakeholder management skills Proactive attitude and ability to work independently Clear ...

Experience with MLOps, model deployment, model monitoring, model lifecycle management, and automated validation processes Experience supporting Generative AI solutions, including RAG architectures, vector search, LLM integration, AI orchestration, or agentic workflows Databricks experience, including Unity Catalog, MLflow, Delta Lake, Lakehouse architecture, and AI tooling Experience working within secure, regulated ...

work with business stakeholders and translate requirements into technical solutions. Desirable Skills & Experience Experience within financial services, banking or financial modelling environments. Experience with LLM-based applications and enterprise AI platforms. Experience implementing AI solutions in production environments. Experience with Azure AI services and Microsoft Copilot technologies. Experience working within ...

Prototype and help harden new modelling approaches, analytical tools, and platform features. Work across the design and build of our internal AI layer, including LLM integrations, MCP servers, and agentic tooling, to automate research workflows and deliver analytical insights within the client‐facing platform. Help with the evolution ...

production, including state management, task execution, model routing, retries and observability Support AI Infrastructure: Work closely with our AI engineers supporting production NLP, LLM and quantitative model workloads, including our in-house GPU infrastructure. Automate Infrastructure: Build and manage Infrastructure-as-Code using Pulumi and automate deployments through GitHub Actions. ...

digital assistants, or conversational platforms (e.g., chatbot deployment, orchestration tools). Hands‐on technical exposure to agentic tool design (function calling, tool registries, MCP), LLM integration patterns (RAG, vector databases, embedding pipelines) and AI observability and monitoring. Experience with process mining and discovery tools (e.g., Celonis, Signavio) to identify ...

patterns, bringing forward new ideas that enhance client delivery and strengthen Wavestone’s internal capability. Qualifications Core Skills & Experience Proven experience building AI/LLM-powered applications in production Deep understanding of AI/GenAI fundamentals, including model behaviour, limitations, and evaluation Experience designing and implementing: RAG systems Agentic workflows ...

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 tooling) Experience operating production distributed systems on AWS/Azure, with a strong grasp of reliability ...

technology The core engineering environment includes: Backend: Python Frontend: React, TypeScript and JavaScript Cloud: Microsoft Azure Databases: PostgreSQL and Cosmos DB AI: Production LLM applications, agentic AI, Claude and OpenAI models AI development tooling: Claude Code and OpenAI Codex Workflow orchestration: Temporal Infrastructure: Terraform and Bicep, supported by an internal ...

platforms (Azure, AWS or GCP), data visualisation tools and MLOps/model deployment practices Understanding of data governance, responsible AI and Generative AI/LLM technologies; relevant professional qualification desirable At BDO, we’ll help you achieve your personal goals and career ambitions, and we have programmes, resources, and frameworks ...

Experience working with relational databases and modern data storage technologies, including graph, vector, or analytical data platforms. Practical experience building and deploying AI/LLM-enabled applications in production environments. Experience with LangGraph, LangChain, agentic workflows, or orchestration frameworks for AI applications; evaluations. Familiarity with modern AI tooling and workflows ...

infrastructure, or applied AI products. Deep expertise in Python, asynchronous programming, system design, and backend engineering fundamentals. Hands-on experience building production systems involving: LLM orchestration or agent frameworks (Pydantic, LangChain, custom orchestration). Data pipelines, ETL, embeddings, or vector search Retrieval-augmented generation (RAG) or model-backed workflows High ...

Python and production software engineering, including APIs, automated testing and cloud-native services. Practical experience building and operating production applications using foundation models and LLM APIs, with a strong understanding of prompt engineering techniques and best practices. Experience with retrieval and embedding pipelines, semantic search or equivalent AI data pipelines. ...

development of AI solutions: design, build, test, and deploy models that are robust, scalable, and used by real users. Apply NLP and LLM techniques to solve real-world problems, ensuring models are optimized for performance and reliability. Continuously improve model quality through tuning, evaluation, and feedback from production usage. Evaluate ...

with Quality Engineers and SREs to ensure solutions meet quality, governance, and operational readiness expectations. Skills Strong Python development experience. Hands‐on experience with LLM and agent frameworks and agentic reasoning patterns. Practical understanding of Model Context Protocol (MCP), including server and tool patterns. FastAPI and REST API design ...

favour simple, maintainable solutions and raise the engineering bar around you. Nice to have: Streaming or event-driven systems for real-time inference. LLM and agent infrastructure (MCP, retrieval-augmented generation, vector stores). Feature stores, model registries and drift detection. AWS experience, particularly managed Airflow (MWAA). ...

helping grow our AI Platform & Reliability Engineering capability.This will include: • AI Platform Strategy & Architecture: Assess, define and evolve enterprise AI platform architectures, covering LLM and agentic frameworks, AI gateways, model lifecycle management, data platforms, MLOps/LLMOps foundations and integration patterns. Support clients in evaluating build, buy and hybrid approaches ...

helping grow our AI Platform & Reliability Engineering capability.This will include: • AI Platform Strategy & Architecture: Assess, define and evolve enterprise AI platform architectures, covering LLM and agentic frameworks, AI gateways, model lifecycle management, data platforms, MLOps/LLMOps foundations and integration patterns. Support clients in evaluating build, buy and hybrid approaches ...

systems and document stores, using OAuth and careful secrets handling. The AI experience You work with the AI/ML team to bring LLM-powered features into the product. You build the Python layer between the product and our AI services, including streaming responses, document processing endpoints and safe access ...

ML. Hands‐on with Azure OpenAI, Azure AI Foundry, Document Intelligence, Data Factory, ML Service, Databricks, Key Vault, Blob Storage, Synapse Analytics, DevOps. Strong LLM, embeddings, RAG, prompt engineering knowledge. Expertise in secure API/event‐driven design, microservices, DDD. Experience with vector databases, semantic search, Azure ML pipelines, Power ...