16 of 16 Remote/Hybrid Prompt Engineering Jobs in the North of England

Title: Senior AI Prompt Engineer (Contract) Location: Sheffield, UK (Hybrid: 2-3 days on-site) Duration: 6 Months (with potential extension) Experience: 5-7 Years Role Overview We are seeking a Senior AI Prompt Engineer to drive enterprise-grade AI solutions across software development and business workflows. This … highly technical role that bridges advanced prompt strategy with hands-on software engineering, focusing on AI-assisted developer productivity and automated system integration. Key Responsibilities Design, optimize, and manage advanced prompts for GitHub Copilot, Microsoft Copilot (M365 & Studio), and Claude/Claude Code. Develop and maintain complex PowerShell ...

Forward Deployed AI Engineer Permanent | Hybrid Leeds | AI Engineering + Forward-Deployed Engineering | Salary up to £100,000 The Opportunity A growing technology consultancy is building an AI-native engineering capability and is looking for a Deployed AI Engineer to help deliver real-world AI solutions … clients. The role combines AI Engineering, Software Engineering and Forward- Deployed Engineering, with ownership across discovery, architecture, build and production. Working in a small delivery pod, the engineer will build directly with client data and within their environments, taking ideas from prototype to MVP in weeks. Between ...

varying learner and employer requirements. AI Adoption & Workplace Application: Support employers to adopt and embed AI technologies within their organisations. Deliver practical training covering: Prompt engineering fundamentals Workflow optimisation using AI Automation opportunities through Copilot Studio and related technologies Promote responsible AI usage, including governance, ethics and data … Proactive, adaptable and solution-focused approach. Desirable Experience delivering AI or digital apprenticeship standards. Experience with Copilot Studio and Power Platform technologies. Knowledge of prompt engineering and AI adoption strategies. Understanding of automation tools and workflow design. Awareness of apprenticeship funding and compliance requirements. Teaching or training qualification ...

varying learner and employer requirements. AI Adoption & Workplace Application: Support employers to adopt and embed AI technologies within their organisations. Deliver practical training covering: Prompt engineering fundamentals Workflow optimisation using AI Automation opportunities through Copilot Studio and related technologies Promote responsible AI usage, including governance, ethics and data … Proactive, adaptable and solution-focused approach. Desirable Experience delivering AI or digital apprenticeship standards. Experience with Copilot Studio and Power Platform technologies. Knowledge of prompt engineering and AI adoption strategies. Understanding of automation tools and workflow design. Awareness of apprenticeship funding and compliance requirements. Teaching or training qualification ...

varying learner and employer requirements. AI Adoption & Workplace Application: Support employers to adopt and embed AI technologies within their organisations. Deliver practical training covering: Prompt engineering fundamentals Workflow optimisation using AI Automation opportunities through Copilot Studio and related technologies Promote responsible AI usage, including governance, ethics and data … Proactive, adaptable and solution-focused approach. Desirable Experience delivering AI or digital apprenticeship standards. Experience with Copilot Studio and Power Platform technologies. Knowledge of prompt engineering and AI adoption strategies. Understanding of automation tools and workflow design. Awareness of apprenticeship funding and compliance requirements. Teaching or training qualification ...

lead the design, architecture, and delivery of AI-powered solutions across client and internal projects. This role bridges business requirements, data science, software engineering, and cloud infrastructure to create scalable, secure, and production-ready AI systems. The ideal candidate combines strong technical expertise with stakeholder management skills … knowledge management systems. Generative AI Experience Design and scale LLM-based applications, including multi-model routing, context management, and cost/latency optimisation. Prompt engineering strategies. Agentic AI systems. RAG design patterns, including chunking strategies, re-ranking, hybrid search, and evaluation Evaluation and monitoring frameworks covering hallucination detection ...

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 ...

GCP. Understand how AI can be embedded into business processes, customer journeys and decision-making, working collaboratively with business, product, design and engineering teams to deliver practical solutions. Support deployment, adoption and change by translating complex technical concepts into clear recommendations and practical experiences for business users, while contributing … ability to apply technology to practical challenges. Data & AI Transformation Experience: Experience in data, analytics, AI or digital transformation through consulting, technology, engineering, academia or industry. Ability to translate business challenges and user needs into practical data and AI solutions. Experience working in Agile or iterative delivery teams, with ...

like token rotation. By leveraging Python, Go, React, and TypeScript, you will create in-house applicationsfrom compliance dashboards to automated release enginesthat solve complex engineering challenges. Automation is central to this role. You will identify repetitive tasks and use AI tools to reduce toil, allowing you to focus … includes an on-call requirement. This role is eligible for inclusion in the Companys hybrid work from home policy. Qualifications Commercial experience in software engineering, DevOps, or platform roles Proficiency in scripting and programming languages such as Python or Bash Strong understanding of version control systems like GitLab ...

information storage and retrieval. Develop agentic reasoning workflows using frameworks like LangChain or LlamaIndex. Lead the full AI lifecycle: data ingestion, embedding, extraction, synthesis, prompt engineering, and workflow orchestration. Deploy, monitor, and maintain models in Docker-based, containerized environments. Collaborate with cross-functional teams to align AI capabilities … databases, and RAG-based architectures. Experience of with agentic frameworks and orchestration frameworks such as LangChain or LlamaIndex. Solid understanding of LLMs, embeddings, and prompt engineering. Highly Desirable: Experience designing multi-agent systems or autonomous workflows. Hands-on experience with Docker and deploying containerised, cloud-native tools. Experience with ...

Financial Services) as a strategic consultant who has delivered several project life cycles.* Technical Knowledge - Hands-on or applied experience with:* Generative AI (LLMs, prompt engineering, RAG, copilots, multimodal AI)* Agentic AI (autonomous agents, multi-agent workflows, tool integration)* Broad strategic knowledge* Scaling AI Experience - Experience designing ...

significant applications across both the Education and Healthcare sectors . They are now looking for a talented Senior Full Stack Developer to join their engineering team and contribute to the continued development of their platform, editor and supporting cloud services. Responsibilities: Build and deliver new functionality across the core … technologies and use cases are introduced Experience: Strong commercial experience with React and Node.js Practical exposure to AI technologies , such as LLMs, prompt engineering, AI APIs, integrations, RAG or orchestration frameworks Understanding of modern AI development concepts including agentic architectures or MCP would be advantageous Good working knowledge ...

proven track record of delivering technology‐enabled or business transformation projects from concept through implementation. Practical, hands‐on experience using generative AI tools and prompt engineering, including developing, testing, and refining prompts for business applications. Experience managing AI, automation, analytics, or digital product initiatives. Strong stakeholder management, facilitation ...

employees across all departments and levels. Educate colleagues on AI fundamentals, responsible usage, governance, data security and best practice. Deliver practical training on prompt engineering techniques to help users maximise AI-generated outputs. Create learning pathways tailored to different business functions and levels of AI maturity. Facilitate workshops ...

tailored to different audiences and skill levels. Create practical enablement experiences, including workshops, hands‐on labs, office hours and self‐service learning content. Develop prompt engineering guidance, best‐practice materials and role‐based use cases that drive meaningful adoption. Embed responsible AI, security and data governance principles into ...

design, development, and deployment of production-grade machine learning systems for global enterprise clients. You'll work at the intersection of research and engineering, translating cutting‐edge papers into scalable, reliable solutions. This is a high‐impact role where you'll mentor junior engineers, shape our ML architecture … stores and data pipelines Stay current with latest ML research and evaluate applicability to client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale using Docker, Kubernetes ...