26 to 50 of 83 Prompt Engineering Jobs in London

technology infrastructure standards. Continuously evaluate emerging technologies, and mentor and elevate team members. Take on related responsibilities as the squad's needs evolve. Requirements: Engineering experience: 10+ years in software engineering, with hands-on AI system design, build or integration, and a track record of taking AI prototypes … 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 via APIs ...

Title: Solutions architect Job Summary The Forward Deployed Engineer (FDE) is a hands-on engineering role focused on building and deploying AI-powered solutions within client environments. Working as part of client-facing delivery teams, this role partnerswith senior engineers, and consulting leads to implement scalable, production-ready systems … HCLTechEnterprise customers. FDEs contribute directly to solution delivery-translating defined requirements into working systems, buildingintegrations, and supporting deployments. While primarily focused on engineering execution, the role alsooperates in client settings, requiring strong collaboration and the ability to support technical discussions withboth engineering and business stakeholders. Key Responsibilities Solution ...

lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. Skills and Competencies - 8+ years of experience in software engineering, with deep hands-on experience designing, coding, testing, and operating scalable, resilient, production-grade backend systems and cloud-native services - Expert-level coding capability … 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 to production, making practical engineering ...

operable after the squad moves on. Keep abreast of new technology developments. Take on related responsibilities as the squad's needs evolve. Requirements: Engineering experience: 3+ years in software engineering, with hands-on experience building LLM-powered applications in production (RAG, tool-augmented agents, or agentic workflows). … Education: BS in Engineering, Computer Science, or equivalent. Ways of working: Comfortable working autonomously within a defined problem and pushing back when something doesn't make sense, and delivering in short, time-boxed cycles where validated outcomes matter more than perfect solutions. Agentic AI/LLMs: Building RAG pipelines ...

machine learning solutions within a global insurance organisation. This is a hands-on technical leadership role, ideal for someone who enjoys combining software engineering, data science, AI, and delivery leadership. You'll help shape the technical direction of a growing AI function while leading the successful delivery of innovative … machine learning, and advanced analytics solutions from concept through production. Provide technical leadership across multiple AI initiatives, ensuring high standards for 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 ...

will be responsible for designing, building and deploying innovative AI-powered applications across the full technology stack. You'll combine hands-on software engineering expertise with deep knowledge of modern AI frameworks, LLMs and agent technologies. The Role Translate business challenges and problem statements into working proofs of concept … Google Cloud AI services, particularly Gemini-based technologies and ecosystems. Advanced Python development skills, with exposure to TypeScript considered highly advantageous. Full-stack software engineering experience, with a strong emphasis on backend development, distributed systems and API design. Hands-on experience building applications using React, Next.js, Svelte or comparable ...

workflows using large language models (LLMs), retrieval-augmented generation (RAG) pipelines and embedding models. Develop scalable backend services and AI integrations, working closely with engineering, architecture and business teams, and support deployment, governance and operational rollout so solutions land production-ready and compliant. What we're looking for Strong … foundations in software or data engineering with hands-on experience delivering AI or AI-enabled solutions. Cloud and modern data infrastructure exposure, plus experience in Financial Services or another regulated industry, is essential. Tech skills include Python, SQL, LLM development (prompt engineering, fine-tuning, RAG), LangChain/ ...

Build and evaluate GenAI/Agentic AI prototypes (Copilot Studio, Azure AI Foundry, Databricks Mosaic AI, Genie, MLflow) Design and tune RAG systems — embeddings, prompt engineering, evaluation Build AI agents using LangChain, LangGraph, AutoGen, and similar frameworks Deploy models via Azure OpenAI, Azure AI Foundry, and Docker Write ...

build scalable, production-ready AI solutions that deliver real business value. Rather than simply developing proofs of concept, you'll be responsible for engineering robust, reusable solutions that become core business capabilities. As a Senior AI Engineer, you'll combine strong full-stack engineering experience with modern … Design reusable components and architecture that can support future AI initiatives across the organisation. Ensure solutions are secure, well-tested, maintainable and aligned with engineering best practice. Provide technical leadership, mentoring and guidance to colleagues whilst remaining hands-on with development. Support and continuously improve production services, identifying opportunities ...

into production environments Develop scalable ML pipelines using AWS cloud technologies Implement MLOps and LLMOps best practices for deployment, monitoring and governance Support feature engineering, model optimisation and performance monitoring Apply responsible AI principles, including model explainability and fairness Present findings and recommendations to technical and non-technical stakeholders … MLOps tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering and RAG architectures Experience with LLMOps tools such as LangChain, LangSmith or LangGraph Strong understanding of model monitoring, validation and governance Excellent ...

/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain ...

Agentic AI prototypes using Azure AI Foundry, Copilot Studio, Databricks Mosaic AI and MLflow. Building, optimising and evaluating Retrieval-Augmented Generation (RAG) solutions using prompt engineering and embedding models. Designing and deploying AI agents using frameworks including LangChain, LangGraph and AutoGen. Delivering production-ready GenAI applications for commercial …/or Scala. Experience with Azure cloud technologies including Azure OpenAI and Azure AI Foundry. Knowledge of Spark Structured Streaming, Autoloader and modern data engineering practices. Experience with ETL/ELT, data modelling and scalable data architectures. Familiarity with Azure Data Factory, Qlik Replicate and data ingestion pipelines. Does ...

Agentic AI prototypes using Azure AI Foundry, Copilot Studio, Databricks Mosaic AI and MLflow. Building, optimising and evaluating Retrieval-Augmented Generation (RAG) solutions using prompt engineering and embedding models. Designing and deploying AI agents using frameworks including LangChain, LangGraph and AutoGen. Delivering production-ready GenAI applications for commercial …/or Scala. Experience with Azure cloud technologies including Azure OpenAI and Azure AI Foundry. Knowledge of Spark Structured Streaming, Autoloader and modern data engineering practices. Experience with ETL/ELT, data modelling and scalable data architectures. Familiarity with Azure Data Factory, Qlik Replicate and data ingestion pipelines. Does ...

Agentic AI prototypes using Azure AI Foundry, Copilot Studio, Databricks Mosaic AI and MLflow. Building, optimising and evaluating Retrieval-Augmented Generation (RAG) solutions using prompt engineering and embedding models. Designing and deploying AI agents using frameworks including LangChain, LangGraph and AutoGen. Delivering production-ready GenAI applications for commercial …/or Scala. Experience with Azure cloud technologies including Azure OpenAI and Azure AI Foundry. Knowledge of Spark Structured Streaming, Autoloader and modern data engineering practices. Experience with ETL/ELT, data modelling and scalable data architectures. Familiarity with Azure Data Factory, Qlik Replicate and data ingestion pipelines. Does ...

experience Desirable Skills Experience using R and NLP or deep learning techniques (e.g., TF-IDF, word embeddings, CNNs, RNNs) Familiarity with generative AI and prompt engineering Experience with Azure Databricks, MLflow, Azure ML services, Docker, or Kubernetes Experience working in large, complex organisations or regulated industries *This role ...

agentic systems comply with AI ethics principles, data regulations, and BFT's governance frameworks. Role Requirements Technical Requisites Interest in large language models (LLMs), prompt engineering, and AI agent architectures. Interest in agentic or multi-agent frameworks (e.g., LangChain, AutoGen, CrewAI, OpenAI Assistants, or equivalent). Proficiency ...

Engineer Software Engineering background is required London, UK | Hybrid - 3 days in office - 12-month contract (Inside IR35) We are seeking a AI Engineer with Software Engineering background to join a fast-moving team working across AI platform engineering and direct collaboration with the Investment Team. … role is split approximately 60/40 between platform engineering and business-facing AI delivery, focusing on building and deploying production-grade AI solutions. We are looking for someone who writes clean, production-quality code and can turn AI capability into real business impact. Key Responsibilities Responsibilities Design, build ...

Full Stack Developer to play a key role in the evolution of their flagship AI platform. This is an opportunity to work on genuine engineering challenges, combining large-scale data processing, production AI systems and modern software engineering to build a platform that customers rely on to make … important commercial decisions. Working within a small, highly experienced engineering team, you'll have significant ownership from day one and help shape both the product and technical direction. The Role This role sits at the intersection of: Large-scale data engineering and entity resolution. Production AI systems that ...

evaluating AI/ML-powered products, including familiarity with evaluation methodologies Understanding of large language models (LLMs) and generative AI concepts, including AI agents, prompt engineering, context management, and Model Context Protocol (MCP), including MCP Apps and their UI capabilities Mastery of AI tools, in particular Claude Desktop … governance, and fostering a culture of responsible AI adoption across the organization. Education Bachelor's/Master's/PhD degree in Computer Science, Engineering, Data Science, Business, or a related field Responsibilities Own the product lifecycle for increasing AI integration across Moody's business services and making Moody ...

will be responsible for designing, building and deploying innovative AI-powered applications across the full technology stack. You'll combine hands-on software engineering expertise with deep knowledge of modern AI frameworks, LLMs and agent technologies. Key Responsibilities Take concepts from problem statement through to working proof-of-concept … technologies, particularly Gemini-based solutions. Strong Python development skills, with TypeScript experience highly desirable. Full stack development experience, with a particular strength in backend engineering and API development. Experience building applications using React, Next.js, Svelte or similar modern front-end technologies. Strong knowledge of SQL, NoSQL and vector databases ...

scalable, secure, and aligned with RELX Responsible AI standards. This is a senior individual-contributor role with broad influence. You will partner closely with Engineering Leads, Product Managers, Data Scientists, and data teams within LNIP. Key Responsibilities: Define and own the AI architecture vision for Protégé in PatentSight+, ensuring … patterns for AI-driven enrichment and classification of patent data at scale, ensuring results are dependable, auditable, and consistent with established IP metrics. Establish prompt engineering standards, evaluation harnesses, and quality frameworks to govern LLM behaviour and maintain output accuracy in production. Partner with Product Management to assess ...

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 … chunking strategies, and retrieval orchestration techniques to improve relevance and answer quality. Support development of semantic search, ranking, and knowledge discovery capabilities. Collaborate with engineering teams to deploy and scale AI-powered solutions. AI Evaluation & Experimentation Develop and apply evaluation frameworks for search and AI systems, including:IR metrics ...

role in rollouts of frontier AI capabilities, ensuring smooth integration with existing IT infrastructure and processes. Accelerate adoption — Work shoulder-to-shoulder with client engineering and product teams to drive meaningful AI adoption, removing blockers and closing skill gaps in real time. Identify patterns and scale — Recognise repeatable deployment … applications with real business impact, ideally in enterprise environments. Practical experience working with large language models (ideally in a enterprise or start-up setting): prompt engineering, agent development, RAG pipelines, evaluation frameworks, workflows, and deployment. Technical Skills Solid programming proficiency (we are open to any experience but primary ...

Azure, GCP, Databricks or similar technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps ...

Architecture or AI Architecture experience. Strong understanding of Generative AI, Large Language Models (LLMs) and AI agent frameworks. Experience designing AI solutions using RAG, prompt engineering and knowledge-grounded architectures. Expertise in Microsoft AI technologies, including Microsoft 365 Copilot, Copilot Studio, Azure AI and/or Power Platform. ...