101 to 125 of 196 Prompt Engineering Jobs in the UK

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 ...

layers - writing high-quality, tested, maintainable code and staying close to implementation rather than delegating it away. Technical Leadership Within the Squad Lead the engineering practice within your delivery team: set coding standards, review designs and pull requests, unblock technically complex problems, and mentor other engineers day to day. … Code" practices to pair with and upskill internal government engineers, so capability genuinely transfers rather than staying locked in the consultancy team. Efficient, Sustainable Engineering Favour low-modality, resource-efficient designs where they meet the need - right-sizing models and infrastructure rather than defaulting to the largest/most ...

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 ...

data landscape, AI is not a siloed experimental lab; it is a core capability that must be embedded into our product DNA and our engineering workflows. We are looking for an AI Enablement Lead who will architect, scale, and own our AI enablement strategy end-to-end. … theoretical researcher or a passive prompt engineer; you are a highly practical, technical driver who builds the foundational platforms, tooling, and frameworks that allow other product and engineering teams to deploy AI safely, rapidly, and at scale. You will democratize AI across the organization, establish modern LLMOps/ ...

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/ ...

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/ ...

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/ ...

Agentic AI, Generative AI and Retrieval-Augmented Generation (RAG) solutions that power intelligent, customer-facing products used globally. Working closely with Product, Platform and Engineering teams, you'll develop production-grade AI systems, autonomous agents and LLM-powered applications, helping shape the future of AI across the organisation. What … agents capable of reasoning, planning and executing complex workflows. Develop multi-agent orchestration, tool integration and advanced retrieval strategies. Optimise LLM performance through prompt engineering, fine-tuning and evaluation. Work with Platform Engineering to deploy scalable AI services using Microsoft Azure. Mentor engineers and contribute ...

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 ...

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 ...

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 ...

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 ...

/ML and Agentic AI platforms - Work across LLMs, RAG, embeddings and semantic search - Support AI deployment, governance and integration patterns - Collaborate with engineering, data, DevOps and business teams - Advise clients on AI platform capability and implementation strategy Tech environment: Python LLMs (prompt engineering, fine-tuning ...

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 ...