1 to 25 of 86 Prompt Engineering Jobs in the UK excluding London

We are looking for a Tech lead who has strong experience insoftware engineering, data engineering,andcloud engineering, with recent leadership in Gen AI and ML solution delivery. Description Accountabilities Collaborate with product teams: Provide technical direction and support for Gen AI solutions across cross-functional groups. Own Gen AI product vision: Define and communicate the technical vision … performance standards. Promote FAIR data principles: Champion findability, accessibility, interoperability, and reusability in data pipelines and Gen AI solutions. Essential Skills/Experience: 10+ years of experience in software engineering, data engineering, and cloud engineering, with recent leadership in Gen AI and ML solution delivery Deep technical mastery in data engineering, software engineering, and cloud … platforms, combined with advanced knowledge of Generative AI systems and frameworks. Expertise in AI engineering principles, including MLOps, prompt engineering, model deployment, and operationalizing large language models (LLMs) Strong knowledge and practical application of DevOps, MLOps, and DataOps methods, processes, and tooling Demonstrated product development and product management experience, with emphasis on Gen AI features and capabilities More ❯

automate processes, improve speed, and enhance decision-making. Role Responsibilities As a Senior AI/ML Engineer, you will: Build & Deploy AI-Driven Software Solutions You'll blend software engineering and AI expertise to develop scalable, production-grade systems leveraging generative AI and agentic automation. Own Project-Based Work Across Diverse Domains You'll tackle varied engagements, ranging in … teams, translating client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities. Leverage Generative AI Expertise Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery. Who We're Looking For Essential Qualifications & Experience Strong software engineering background … with deep experience deploying scalable systems At least some commercial experience using Generative AI exposure (e.g., LLMs, agentic interfaces, prompt engineering) but primarily strong engineering fluency Comfortable with project-based, delivery-focused work, even if no prior consultancy experience Confident in client-facing situations and able to collaborate effectively with non-technical stakeholders Reliable, consistent work history More ❯

that automate processes, improve speed, and enhance decision-making. Role Responsibilities As a Senior AI Applied Engineer, you will: Build & Deploy AI-Driven Software Solutions You’ll blend software engineering and AI expertise to develop scalable, production-grade systems leveraging generative AI and agentic automation. Own Project-Based Work Across Diverse Domains You’ll tackle varied engagements, ranging in … teams, translating client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities. Leverage Generative AI Expertise Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery. Who We're Looking For Essential Qualifications & Experience Strong software engineering background … with deep experience deploying scalable systems At least some commercial experience using Generative AI exposure (e.g., LLMs, agentic interfaces, prompt engineering) but primarily strong engineering fluency Comfortable with project-based, delivery-focused work, even if no prior consultancy experience Confident in client-facing situations and able to collaborate effectively with non-technical stakeholders Reliable, consistent work history More ❯

that automate processes, improve speed, and enhance decision-making. Role Responsibilities As a Senior AI Applied Engineer, you will: Build & Deploy AI-Driven Software Solutions You’ll blend software engineering and AI expertise to develop scalable, production-grade systems leveraging generative AI and agentic automation. Own Project-Based Work Across Diverse Domains You’ll tackle varied engagements, ranging in … teams, translating client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities. Leverage Generative AI Expertise Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery. Who We're Looking For Essential Qualifications & Experience Strong software engineering background … with deep experience deploying scalable systems At least some commercial experience using Generative AI exposure (e.g., LLMs, agentic interfaces, prompt engineering) but primarily strong engineering fluency Comfortable with project-based, delivery-focused work, even if no prior consultancy experience Confident in client-facing situations and able to collaborate effectively with non-technical stakeholders Reliable, consistent work history More ❯

that automate processes, improve speed, and enhance decision-making. Role Responsibilities As a Senior AI Applied Engineer, you will: Build & Deploy AI-Driven Software Solutions You’ll blend software engineering and AI expertise to develop scalable, production-grade systems leveraging generative AI and agentic automation. Own Project-Based Work Across Diverse Domains You’ll tackle varied engagements, ranging in … teams, translating client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities. Leverage Generative AI Expertise Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery. Who We're Looking For Essential Qualifications & Experience Strong software engineering background … with deep experience deploying scalable systems At least some commercial experience using Generative AI exposure (e.g., LLMs, agentic interfaces, prompt engineering) but primarily strong engineering fluency Comfortable with project-based, delivery-focused work, even if no prior consultancy experience Confident in client-facing situations and able to collaborate effectively with non-technical stakeholders Reliable, consistent work history More ❯

LLMs, retrieval-augmented architectures, embedding pipelines, agents) from prototype to production. Lead the full ML lifecycle: data extraction, modelling, fine-tuning, training, inference, deployment, and monitoring. Collaborate with product, engineering, and data teams to translate business needs into working AI solutions. Establish standards for prompt engineering, model evaluation, and responsible AI (governance, bias mitigation, safety). Optimise … models for scalability, latency, cost, and accuracy in live environments. Mentor engineers and raise the overall technical bar of the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and … prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. Solid engineering fundamentals: version control, CI/CD for ML, observability, API integration, and cloud infrastructure (AWS/Azure/GCP). Confident communicator able to explain complex trade-offs to non-technical stakeholders. UK-based and available for two days per week in the More ❯

LLMs) for real-world applications. Develop and optimise pipelines for data collection, preprocessing, and model evaluation. Collaborate with product engineers to deploy models into scalable production systems. Experiment with prompt engineering, RAG architectures, and multimodal models. Contribute to internal tools for monitoring, testing, and improving AI performance. Stay on the edge of ML/AI research — we give … Natural Language Processing, Large Language Models, Generative AI, GenAI, Neural Networks, PyTorch, TensorFlow, Hugging Face, OpenAI, LangChain, RAG, Retrieval-Augmented Generation, Python, Data Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud, AI Infrastructure, Transformers, Reinforcement Learning, Vector Databases, Pinecone, Weaviate, Semantic Search, API Development, AI Deployment, Model Serving, AI More ❯

LLM-based applications in secure, production-ready environments Integrate front-end components with AI models and back-end logic to deliver seamless, end-to-end functionality Perform data and prompt engineering to optimize model performance and outputs Optimize applications for performance, scalability, and security Collaborate cross-functionally with engineering, product, and AI teams to deliver high-impact … databases, including PostgreSQL, Redis, or MongoDB Solid understanding of containerised microservice infrastructure Working knowledge of Kubernetes, security best practices, and cloud platforms (AWS, GCP, or Azure) Desirable: Experience with prompt engineering, Retrieval-Augmented Generation (RAG), and graph databases Familiarity with multi-agent LLM systems and agentic platforms (e.g., AutoGen, CrewAI), and experience deploying LLM-based applications Experience with … LLM applications that deliver measurable business value Maintain low latency, high system uptime, and strong performance across APIs and AI services Drive fast, iterative collaboration across product, design, and engineering teams Continuously improve the platform through testing, research, and integration of modern AI and software practices Why Join Us? Join a mission-driven, high-growth AI startup shaping the More ❯

LLM-based applications in secure, production-ready environments Integrate front-end components with AI models and back-end logic to deliver seamless, end-to-end functionality Perform data and prompt engineering to optimize model performance and outputs Optimize applications for performance, scalability, and security Collaborate cross-functionally with engineering, product, and AI teams to deliver high-impact … databases, including PostgreSQL, Redis, or MongoDB Solid understanding of containerised microservice infrastructure Working knowledge of Kubernetes, security best practices, and cloud platforms (AWS, GCP, or Azure) Desirable: Experience with prompt engineering, Retrieval-Augmented Generation (RAG), and graph databases Familiarity with multi-agent LLM systems and agentic platforms (e.g., AutoGen, CrewAI), and experience deploying LLM-based applications Experience with … LLM applications that deliver measurable business value Maintain low latency, high system uptime, and strong performance across APIs and AI services Drive fast, iterative collaboration across product, design, and engineering teams Continuously improve the platform through testing, research, and integration of modern AI and software practices Why Join Us? Join a mission-driven, high-growth AI startup shaping the More ❯

Advantage are recruiting on behalf of our global energies client for an NLP/GenAI Data Scientist who can bring a strong understanding in modern NLP, LLMs, transformer architectures, prompt-engineering, RAG, agentic architectures and evaluation methodologies.They require candidates to offer strong knowledge of Python programming for developing and debugging AI models and would expect suitable candidates to … be educated to a Degree if not Masters level (computer science, electrical engineering, or a related technical subject) though you’ll still be considered without an MSc. Background Generative AI (GenAI) is seen as having the potential to revolutionise our client’s operations across all major lines of business. Applications may include conversational AI, intelligent information retrieval, AI-assisted … with stakeholders, project managers, and architects to gather requirements, plan project scopes, and deliver projects within agreed timelines. Candidate Requirements Experience and understanding of modern NLP, LLMs, transformer architectures, prompt-engineering, RAG, agentic architectures and evaluation methodologies. Strong knowledge of Python programming for developing and debugging AI models. Excellent communication skills and a collaborative mindset with the ability More ❯

Advantage are recruiting on behalf of our global energies client for an NLP/GenAI Data Scientist who can bring a strong understanding in modern NLP, LLMs, transformer architectures, prompt-engineering, RAG, agentic architectures and evaluation methodologies. They require candidates to offer strong knowledge of Python programming for developing and debugging AI models and would expect suitable candidates … to be educated to a Degree if not Masters level (computer science, electrical engineering, or a related technical subject) though you’ll still be considered without an MSc. Background Generative AI (GenAI) is seen as having the potential to revolutionise our client’s operations across all major lines of business. Applications may include conversational AI, intelligent information retrieval, AI … with stakeholders, project managers, and architects to gather requirements, plan project scopes, and deliver projects within agreed timelines. Candidate Requirements Experience and understanding of modern NLP, LLMs, transformer architectures, prompt-engineering, RAG, agentic architectures and evaluation methodologies. Strong knowledge of Python programming for developing and debugging AI models. Excellent communication skills and a collaborative mindset with the ability More ❯

delivery models the Trainer will support digital transformation by upskilling individuals to become in-house digital enablers, combining technical expertise with change management, risk mitigation, ethical AI use, and prompt engineering skills. The role includes delivering a blend of face-to-face workshops, online training, hands-on labs, and ongoing consultancy-style support aligned to apprenticeship standards. Role … an extended transformation journey, guiding them through real-world activities such as Copilot deployment, semantic indexing, data governance, and AI workflow automation. Coach staff in critical skills such as prompt engineering, AI risk mitigation, ethical considerations, and change leadership to ensure responsible, scalable adoption. Align learning delivery with organisational needs, helping teams to build AI adoption roadmaps, configure More ❯

Desirable requirements Experience working with IPaas/Digital orchestration platforms. I.e.- Azure logic apps, Conscia, Boomi, Celigo etc. Experience working with low code/no code platforms Experience with prompt engineering- experience designing and optimising prompts Experience using service bus and message queues Experience supporting and troubleshooting build pipelines Ability to take ownership of project work and take … initiative where required Experience in monitoring & observing application errors and performance Experience working on accessibilityExperience with prompt engineering Experience working with databases - SQL Server, Cosmos DB Benefits When you join Renishaw, we're committing to your future career. That's because we believe in developing our people's skills and promoting them internally. We also offer a benefits More ❯

Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java … experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g. … MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field. More ❯

Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java … experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g. … MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field. More ❯

Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java … experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g. … MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field. More ❯

Prompt Engineer - LLMs & Responsible AI £775/day Inside IR35 | End of FY | Hands-on Prompt Engineer needed for a government AI programme. Design and evaluate prompts across multiple LLMs (ChatGPT, Claude) to support policy and business use cases. The Role Craft and refine prompts using advanced techniques (ReAct, Chain-of-Thought, ART) Build multi-agent workflows and … context-aware LLM systems Advise on responsible AI practices and risk mitigation Collaborate with policy professionals and user researchers Essential Skills Proven prompt engineering experience across multiple LLMs Multi-agent systems and tool-augmented workflows Deep understanding of LLM failure modes and responsible AI Ability to translate technical concepts for non-technical stakeholders The Details Rate: £775/ More ❯

powered by AI. You'll work across the full stack using modern web technologies and contribute to a platform where AI is deeply integrated into the user experience and engineering workflows. This role offers the opportunity to deepen your technical skills, expand your experience with cloud-native and AI-integrated systems, and collaborate closely with experienced engineers, designers, and … full stack development, particularly with React, TypeScript, Node.js, Next.js, and database technologies such as PostgreSQL. Experience working with cloud infrastructure, preferably with Azure or Vercel. Solid understanding of software engineering principles, web architecture, and performance optimisation. Familiarity with integrating and consuming AI models via APIs. Experience building and consuming RESTful and/or GraphQL APIs. Knowledge of automated testing … of advanced development environments and AI-powered tooling such as Cursor, with an emphasis on increasing velocity, improving code quality, and leveraging contextual AI assistance in day-to-day engineering workflows. Exposure to incorporating LLMs into engineering workflows for production-ready applications, including prompt engineering and context management. Familiarity with multiple LLM providers (e.g. OpenAI, Anthropic More ❯

of AI solution development from concept to deployment and maintenance. Utilize programming skills in Python to automate processes and enhance functionality. Work with large datasets for data preprocessing, feature engineering, and model evaluation. Develop and maintain REST APIs and microservices architectures. Monitor, evaluate, and apply governance frameworks for AI/ML models in production environments. Prepare technical documentation and … effectively communicate complex concepts to both technical and non-technical stakeholders. Required Skills & Qualifications: Minimum 3 years of experience in AI solution engineering, specifically in enterprise environments. Demonstrable experience with Microsoft Azure AI services, including AI Foundry and Microsoft Copilot Studio. Proficiency in Python and familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Experience with … Large Language Models, prompt engineering, and RAG implementations. Strong skills in data analytics, API development, and MLOps practices including CI/CD for ML. Excellent technical documentation and communication skills. Desirable knowledge in Docker, Kubernetes, and understanding of financial services or regulatory environments. In the first instance, please submit your CV. More ❯

skills in Python, JavaScript, or similar languages. LLM & Agent Expertise: Hands-on experience with LLMs (OpenAI, Anthropic, Mistral) and agent frameworks. Advanced Tools: Familiarity with vector databases, RAG pipelines, prompt engineering, REST APIs, cloud deployment, and containerization (Docker/Kubernetes). Domain Knowledge: Experience in one or more business domains such as finance, housing, operations, or customer service. More ❯

skills in Python, JavaScript, or similar languages. LLM & Agent Expertise: Hands-on experience with LLMs (OpenAI, Anthropic, Mistral) and agent frameworks. Advanced Tools: Familiarity with vector databases, RAG pipelines, prompt engineering, REST APIs, cloud deployment, and containerization (Docker/Kubernetes). Domain Knowledge: Experience in one or more business domains such as finance, housing, operations, or customer service. More ❯

nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, Tensorflow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on cloud like Azure, AWS or GCP is preferred. Foundational Knowledge: A strong foundation in statistics … mathematics, AI principles and programming is essential for success in this role. Ideally, you will also have Problem-Solving: Ability to translate business assumptions and rules into feature engineering and model explainability, addressing business problems with data-driven solutions. Collaborative Development: Work under the guidance of senior data scientists and solution architects to build models that align with strategic More ❯

teams to align AI projects with business priorities Share knowledge and mentor colleagues on AI and automation best practices Skills & Experience Degree or background in Computer Science, AI, Software Engineering, or Data Science Strong programming skills (e.g. Python, JavaScript, JSON) Awareness of AI/ML concepts, Large Language Models and prompt engineering Experience with cloud platforms (Azure More ❯

teams to align AI projects with business priorities Share knowledge and mentor colleagues on AI and automation best practices Skills & Experience Degree or background in Computer Science, AI, Software Engineering, or Data Science Strong programming skills (e.g. Python, JavaScript, JSON) Awareness of AI/ML concepts, Large Language Models and prompt engineering Experience with cloud platforms (Azure More ❯

practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, Hugging Face, vLLM, MCP, prompt engineering) Excellent communication skills and ability to explain ML concepts to non-technical stakeholders Ability to work effectively in multi-disciplinary teams, collaborating across engineering, product, and More ❯