76 to 100 of 138 Prompt Engineering Jobs in England

making across complex digital transformation programmes. With access to cutting edge AI frameworks, high performance computing environments, and modern data platforms, you will guide engineering and data science teams in building secure, scalable, and ethical AI systems. This role empowers you to shape end to end AI ecosystemsaccelerating delivery … Your responsibilities: (Up to 10, Avoid repetition) Define the enterprise AI architecture vision and reference patterns; align them to business goals, risk posture, and engineering standards across cloud and hybrid environments. Design secure, scalable AI solutions covering data ingestion, feature engineering, model training, inference, and continuous feedback loops. ...

making across complex digital transformation programmes. With access to cutting edge AI frameworks, high performance computing environments, and modern data platforms, you will guide engineering and data science teams in building secure, scalable, and ethical AI systems. This role empowers you to shape end to end AI ecosystemsaccelerating delivery … Your responsibilities: (Up to 10, Avoid repetition) Define the enterprise AI architecture vision and reference patterns; align them to business goals, risk posture, and engineering standards across cloud and hybrid environments. Design secure, scalable AI solutions covering data ingestion, feature engineering, model training, inference, and continuous feedback loops. ...

making across complex digital transformation programmes. With access to cutting-edge AI frameworks, high-performance computing environments, and modern data platforms, you will guide engineering and data science teams in building secure, scalable, and ethical AI systems. This role empowers you to shape end-to-end AI ecosystemsaccelerating delivery … more intelligent, AI-enabled future. Your responsibilities: Define the enterprise AI architecture vision and reference patterns; align them to business goals, risk posture, and engineering standards across cloud and hybrid environments. Design secure, scalable AI solutions covering data ingestion, feature engineering, model training, inference, and continuous feedback loops. ...

driven efficiency, innovation or automation opportunities maintaining alignment with business goals, regulatory or compliance requirements and ethical principles. Solution Design: Partner with product and engineering teams to translate business requirements into scalable AI solutions. Lead the evaluation, selection, and integration of AI platforms and models, tools, and technologies. Ensure … emerging AI trends, technologies, protocols, research breakthroughs, model development and AI software design pattern and best practices. Provide technical guidance and mentorship to the engineering teams. Collaboration and Communication: Foster strong relationships with stakeholders, including business leaders, product managers. Collaborate with senior leadership to align AI initiatives with organizational ...

advanced machine learning and generative AI solutions that deliver real-world impact across complex, high-stakes domains. You will be embedded within a multidisciplinary engineering team, working across the end-to-end delivery of machine learning systems. This includes building models, running experiments, and deploying scalable solutions using modern … models into production environments Building and maintaining ML pipelines using AWS services Assisting in the development of GenAI/LLM-based applications (e.g. prompt engineering, RAG pipelines) Implementing best practices in experiment tracking, model versioning, and reproducibility Monitoring model performance and supporting continuous improvement Collaborating with engineers, data ...

modern MLOps/LLMOps practices, including experiment tracking, versioning, and deployment on cloud platforms Influence technical direction and best practice in ML and AI engineering Mentor and support junior engineers and graduates Engage directly with clients to scope, design, and deliver operationally-ready AI and ML solutions Key Responsibilities … SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Ability to absorb complex scientific and technical concepts and apply them to operational solutions Strong communication skills for both technical ...

delivery Required Experience Proven experience as an AI Architect/Machine Learning Architect/GenAI Architect Hands-on expertise with LLMs, RAG, LangChain, LangGraph, prompt engineering Strong cloud experience: Azure OpenAI, AWS Bedrock/SageMaker or GCP Vertex AI Experience with Kubernetes, Docker, microservices, API integration Strong knowledge ...

Demonstrated experience as an AI Architect, Machine Learning Architect, or Generative AI Architect Strong hands-on expertise with LLMs, RAG architectures, LangChain, LangGraph, and prompt engineering Deep cloud knowledge including Azure OpenAI, AWS Bedrock/SageMaker, or GCP Vertex AI Experience with Kubernetes, Docker, microservices architectures ...

tangible mark on how people develop their careers. This is a role for someone who's done real AI work inside a high-calibre engineering organisation and worked closely with product. What you'll do Design and deploy LLM/RAG systems (GPT, Claude, Gemini) powering content generation, semantic … model in a notebook you've taken it to real users, measured it, and iterated. You've done this inside organisations that take engineering seriously. Whether that's a top-tier tech company, a defence/intelligence-grade AI startup, or a fast-scaling data-led business you know ...

variety of generative models Indepth experience in finetuning and customizing pretrained AI models with good understanding of various patterns and practices in AI data engineering and large data processing Handson in Prompt Engineering Azure Open AI Form Recognizer Cognitive Search Vector Databases Develop and deliver upskilling sessions ...

optimise machine learning and NLP models in production Develop end-to-end data science pipelines Design and prototype Generative AI solutions (LLMs, embeddings, prompt engineering) Work with BigQuery ML and cloud platforms for large-scale modelling Translate business challenges into scalable data solutions Collaborate with cross-functional teams … across engineering and business Mentor junior team members where required Required Experience 10+ years in Data Science, Machine Learning, or AI Engineering Strong Python skills and experience with ML frameworks Proven track record delivering end-to-end ML/NLP solutions Hands-on experience with Generative AI (LLMs ...

decision-making across complex digital transformation programmes. Access to cutting-edge AI frameworks, high-performance computing environments, and modern data platforms, you will guide engineering and data science teams in building secure, scalable, and ethical AI systems. This role empowers you to shape end-to-end AI ecosystems—accelerating … provenance. Select and standardize frameworks (e.g., LangGraph, Google ADK, MCP, A2A patterns). Hands-on expertise with agentic frameworks (orchestrators). Experience with LLMs, prompt engineering, tool/function calling, memory management. API-first integration, event-driven architectures, and data pipelines. Experience on Google Cloud Platform (preferred ...

deliver AI-powered client solutions, including RAG pipelines, agent architectures, LLM integrations, and protocol-driven tooling Build scalable AI systems using modern software engineering best practice (clean code, testing, CI/CD) Develop internal AI tooling to accelerate engineering delivery Lead advanced AI knowledge-sharing sessions within internal … upskilling initiatives Evaluate emerging AI frameworks, protocols, and tooling Support pragmatic AI adoption across multidisciplinary engineering teams AI Engineer Requirements Essential: Strong software engineering foundations with a production mindset Proven hands-on experience with Large Language Models (LLMs), including API integrations, prompt engineering, agent workflows ...

DevOps practices and the integration of large language models into secure, production-grade systems. You'll be working on emerging technologies, solving real-world engineering challenges, and contributing to the evolution of AI capabilities in a regulated setting. Key Responsibilities Design, build, and maintain backend services and APIs that … provide secure access to AI capabilities Develop Python-based components for prompt orchestration, output validation, and evaluation workflows Integrate LLMs into existing enterprise systems, ensuring alignment with security and observability standards Implement and manage CI/CD pipelines in line with engineering best practices Collaborate with cross-functional ...

powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices, including model explainability … governance and quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help ...

connections-of signal. • Analytics: Build closed-loop reporting: which signals, channels, and segments drive qualified meetings and revenue. What You Will NOT Own: • Product engineering: Loctax has a separate product engineering team of ~8 people. You do not build product features. • Closing deals: The sales team handles … structured prompts, parsing JSON responses, handling errors, and managing the boundary between what the AI decides and what the code enforces. This is not prompt engineering in a chat window; it is integrating AI as a component in a data pipeline. • SQL: Strong Postgres SQL. You will write ...

automation templates Help establish internal AI standards and best practices Tech Environment AI & Agents Advanced reasoning models (e.g. Claude) Code generation models (e.g. Codex) Prompt engineering & evaluation frameworks RAG architectures Embeddings & vector search (desirable) Orchestration & Automation Agent orchestration frameworks (e.g. Antigravity) Power Automate API-first integrations Event-driven … architectures Engineering Python REST APIs SQL Git-based version control Secure secrets handling What We’re Looking For 5–8+ years in automation engineering, AI systems, or solutions architecture Experience deploying LLM-powered workflows in production Proven ability to automate complex business processes end-to-end Experience integrating ...

company of the people they work with, then youve come to the right place! Role description: This is not a slide-making or prompt-engineering role. We are looking for someone who has built multi-agent AI systems that run in production - not demos, not pilots that died … teams Prepare and present technical proposals, POC plans, and roadmaps - own the story end-to-end Team & Practice Mentor junior AI engineers; raise AI engineering quality across the delivery team Stay current: evaluate new models, frameworks, and tooling before the hype catches up Contribute to internal knowledge bases, reusable ...

directly enhance the Ultralytics HUB platform and empower our global community of developers and researchers. 🛠️ Skills and Experience 5+ years of experience in software engineering, with a strong focus on AI and Machine Learning (ML). Expert-level proficiency in Python and deep learning frameworks, particularly PyTorch. Proven experience … experience with the full RAG pipeline, including vector embeddings , rerankers , and data indexing in databases like MongoDB. Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization. Familiarity with MLOps principles and tools, including CI/CD with GitHub Actions . A strong interest in computer vision ...

experimentation and prototyping of advanced ML/AI techniques · Provide technical direction, mentoring, and hands-on guidance to the data science team. · Work with engineering, product, and business stakeholders to align ML strategy with business goals. · Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability … years in a technical lead role. · Deep experience in training and deploying computer vision models into production · Proven track record with LLM fine-tuning, prompt engineering and productionisation · Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. · Strong coding skills in Python, with ...

GenAI tooling Own and evolve the AI strategy, driving real product impact through LLMs, agentic architectures, and advanced ML Work cross-functionally with Product, Engineering and leadership to turn customer problems into production AI systems Influence the adoption of state-of-the-art approaches across RAG pipelines, evaluation frameworks … agent tooling, and prompt engineering Build AI products that deliver real commercial value, balancing experimentation with scalable delivery What they’re looking for: Proven AI leader who has built commercial AI products Deep experience across Generative AI, LLMs and classical machine learning Strong hands-on engineering background ...

analysis of business problems, workflows, processes and decision points to determine where AI can improve outcomes, efficiency or customer experience. Design AI enabled workflows, prompt patterns, user interactions and human in the loop models that maximise safety, transparency and user trust. Assess solution feasibility by evaluating data readiness, technical … mapping processes, decision flows and user journeys to identify where AI, automation or Copilot can add value. Understanding of core AI concepts including LLMs, prompt engineering, automation, decision support and responsible AI. Experience assessing data quality, readiness, lineage and feasibility for AI enabled solutions. Ability to design ...

analysis of business problems, workflows, processes and decision points to determine where AI can improve outcomes, efficiency or customer experience. Design AI enabled workflows, prompt patterns, user interactions and human in the loop models that maximise safety, transparency and user trust. Assess solution feasibility by evaluating data readiness, technical … mapping processes, decision flows and user journeys to identify where AI, automation or Copilot can add value. Understanding of core AI concepts including LLMs, prompt engineering, automation, decision support and responsible AI. Experience assessing data quality, readiness, lineage and feasibility for AI enabled solutions. Ability to design ...

systems Can demonstrate experience of building GenAI solutions, understands the capabilities and concepts of LLMs, such as AI agents, and has knowledge of prompt engineering techniques Works independently, resolving complex issues with little or no supervision or direction Has experience of managing a junior team to achieve ...

Company They are a tech‐forward insurance organisation with a strong focus on delivering smarter, more personalised digital products. Their teams combine data, engineering and customer expertise to create solutions that simplify complex challenges for their users. Innovation, collaboration and a flexible working culture are at the heart … secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP. • Embed security, compliance, GDPR controls and best‐practice engineering with clear documentation and stakeholder collaboration. Your Skills and Experience To be successful, you will bring: • Strong Python skills for backend services, SDKs ...