26 to 50 of 519 Prompt Engineering Jobs in the UK

Machine Learning problems on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, focusing on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with Git and using Docker for containerization. Knowledge of Databricks. Effective communication within cross-functional teams and More ❯

machine learning solutions on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, focusing on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with Git and using Docker for containerization. Knowledge of Databricks. Excellent communication skills, with the ability to More ❯

problems on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, with a focus on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with Git and using Docker for containerization. Knowledge of Databricks. Communicating effectively within cross-functional teams and More ❯

We are not accepting agency submissions for this role. Job Purpose At tiQtoQ , we're passionate about redefining engineering and AI automation. As part of our continuous evolution, we're looking for an AI Engineer to join our team. You will develop robust, scalable, and intelligent agentic systems that integrate seamlessly into software development lifecycles (SDLC). You'll … lead the charge in developing LLM-powered agents, assistants, custom tooling for developers, and AI automation frameworks. This is a hands-on role that combines software engineering, A experimentation, and AI product innovation. You'll be empowered to shape agent architecture, explore cutting-edge frameworks like LangChain and LlamaIndex, and be responsible for operationalising high-performance, real-time AI … systems. Key Responsibilities LLM Agent Development : Design and build intelligent, multi-step LLM agents using frameworks like LangChain, LangGraph, LlamaIndex or similar to support engineering workflows. AI Assistant & Tool Innovation: Build AI-powered agents, assistants, and tools that streamline workflows and enhance user productivity. Have a deep understanding of how these systems function under the hood and contribute to More ❯

Integrate AI agents with enterprise systems via APIs, databases, and automation tools. Experiment rapidly to improve AI-driven interactions, response quality, and automation capabilities. Collaborate with cross-functional teams (engineering, research, and product) to shape Eloquent AI’s roadmap. Monitor and improve agents’ performance via user simulations and evaluations. Requirements: 3+ years of experience in software development or AI … engineering in a production environment. Strong proficiency in Python, with experience in frameworks like PyTorch and TensorFlow. Experience working with LLMs or large computer vision models, or generative AI models, including fine-tuning and inference optimization. Familiarity with APIs, cloud infrastructure (AWS, GCP, or Azure), and enterprise integrations. Ability to prototype, experiment, and iterate quickly to improve AI agents. … and the ability to work closely with customers to refine AI solutions. Solid mathematical foundation of machine learning and deep learning techniques Bonus Points If... You have experience with prompt engineering, parameter-efficient fine-tuning (PEFT), retrieval-augmented generation (RAG), reinforcement learning for LLMs. You’ve published AI research in top tier AI conferences like: NeurIPS, ACL, SIGIR More ❯

AI algorithms for predictive analytics, recommendation engines, and automation in professional services. Apply machine learning (ML) and deep learning (DL) techniques to enhance decision-making and business intelligence. Data Engineering & Integration Architect robust data pipelines to support AI model training and inference. Implement automated data collection, integration, cleansing, and transformation techniques to ensure high-quality data inputs. Collaborate with … data engineering teams to align AI solutions with real-world business applications. AI Model Training, Evaluation & Performance Optimization Train AI models using supervised, unsupervised, and reinforcement learning techniques , refining them based on business insights . Define model performance metrics to ensure AI solutions deliver tangible value. Real-Time AI Applications & System Integration Work alongside software engineers and business consultants … non-technical stakeholders. Mandatory Qualifications & Skills Bachelor's or master's degree in Computer Science, AI, Data Science, or related fields . Expertise in large language models (LLMs) and prompt engineering for business applications. Strong programming skills ( Python, R, Java ) for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying More ❯

AI algorithms for predictive analytics, recommendation engines, and automation in professional services. Apply machine learning (ML) and deep learning (DL) techniques to enhance decision-making and business intelligence. Data Engineering & Integration Architect robust data pipelines to support AI model training and inference. Implement automated data collection, integration, cleansing, and transformation techniques to ensure high-quality data inputs. Collaborate with … data engineering teams to align AI solutions with real-world business applications. AI Model Training, Evaluation & Performance Optimization Train AI models using supervised, unsupervised, and reinforcement learning techniques , refining them based on business insights . Define model performance metrics to ensure AI solutions deliver tangible value. Real-Time AI Applications & System Integration Work alongside software engineers and business consultants … non-technical stakeholders. Mandatory Qualifications & Skills Bachelor's or master's degree in Computer Science, AI, Data Science, or related fields . Expertise in large language models (LLMs) and prompt engineering for business applications. Strong programming skills ( Python, R, Java ) for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying More ❯

our Glassdoor score is pretty mega too! Are you a seasoned AI expert ready to take your skills to the next level? Do words like Azure OpenAI, Cognitive Services, prompt engineering, Retrieval-Augmented Generation (RAG) architectures, vector stores, and API integrations make you light up inside? If so, we want to hear from you! At 1st Central , we … too!). It's about bringing smart ideas to life and making a real impact. You'll be at the heart of our AI strategy - from initial concept and prompt design, through development and testing, to deployment, production, monitoring and continuous improvement optimising cutting-edge AI solutions across the business. One day you might be collaborating with our Data … can simplify processes, enhance experiences, or save time-and you know how to turn those ideas into working solutions. What's involved: Lead the design and implementation of AI engineering frameworks and standards, emphasising API integrations, Azure infrastructure, and Azure security & networking. Architect and develop AI and Generative AI solutions using services like Azure OpenAI and Azure Cognitive Services More ❯

our Glassdoor score is pretty mega too! Are you a seasoned AI expert ready to take your skills to the next level? Do words like Azure OpenAI, Cognitive Services, prompt engineering, Retrieval-Augmented Generation (RAG) architectures, vector stores, and API integrations make you light up inside? If so, we want to hear from you! At 1st Central , we … too!). It's about bringing smart ideas to life and making a real impact. You'll be at the heart of our AI strategy - from initial concept and prompt design, through development and testing, to deployment, production, monitoring and continuous improvement optimising cutting-edge AI solutions across the business. One day you might be collaborating with our Data … can simplify processes, enhance experiences, or save time-and you know how to turn those ideas into working solutions. What's involved: Lead the design and implementation of AI engineering frameworks and standards, emphasising API integrations, Azure infrastructure, and Azure security & networking. Architect and develop AI and Generative AI solutions using services like Azure OpenAI and Azure Cognitive Services More ❯

with business and product goals. Drive performance and cost optimisation for all AI systems. Document processes for a range of audiences Contribute to a collaborative, low-ego, high-performance engineering culture. About You Strong background in software engineering and production-grade systems. Expertise in Python (both backend and AI/ML use cases). Experience designing, building, and … deploying LLM-powered applications in production. Familiarity with transformer architectures and practical handling of LLM context, prompt chaining, and prompt engineering. Hands-on experience with MLOps tools like MLflow, Weights & Biases, and orchestration platforms like Kubeflow or Databricks. Deep understanding of cloud platforms (especially Azure and AWS), containers, microservices, and event-driven architecture. Strong problem-solving and debugging More ❯

with ML models to building robust, scalable software systems that integrate these intelligent features. This is an exciting opportunity to contribute to impactful projects at the intersection of software engineering and artificial intelligence, with the flexibility of short-term engagements. Key Responsibilities: • Design, develop, test, deploy, and maintain robust and scalable software applications and infrastructure. • Research, implement, and evaluate … machine learning models (including deep learning and potentially reinforcement learning) to address specific business challenges. • Work with Large Language Models (LLMs): fine-tuning, prompt engineering, developing Retrieval-Augmented Generation (RAG) systems, and integrating LLM capabilities into applications via APIs. • Process, clean, and analyze large datasets to prepare them for model training and evaluation. • Develop APIs and services to … requirements, design solutions, and deliver high-quality features. • Implement MLOps practices for model versioning, deployment, monitoring, and lifecycle management. • Write clean, maintainable, well-documented, and tested code following software engineering best practices (e.g., SOLID principles, CI/CD). • Stay current with the latest advancements in AI, ML, LLMs, and software engineering trends and technologies. • Troubleshoot and debug More ❯

the Analysis Team to develop and deploy ML (including LLM) models that enhance our 3D design/GIS platforms and internal tooling. Collaborate with cross-functional teams including Product, Engineering, and Data Engineering to translate business challenges into scalable ML solutions. Collaborate with external AI specialists to deliver larger-scale projects. Explore, clean, and transform large datasets for … communication on changing goals, plans, or requirements. What you'll need to succeed: Hands-on experience working with LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments. Strong proficiency in Python, with expertise in using frameworks like Hugging Face Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools. … AWS ecosystem (SageMaker, Lambda, etc.). Strong understanding of data structures, algorithms, and statistical analysis. Experience working with ETL pipelines and structured/unstructured data. Solid grasp of software engineering principles, version control systems (Git), and Agile methodologies. Ability to break down complex data challenges into clear, manageable tasks. Clear communicator and problem solver with a positive, proactive attitude. More ❯

experiments using the latest ML technologies; analyse results and fine-tune models. Write production-level code in Python, transforming experimental outcomes into real-world applications by closely collaborating with engineering teams. Take ownership of end-to-end development for both proof-of-concept work and production-ready solutions. Improve system accuracy and efficiency by identifying performance issues and removing … bottlenecks. Partner with product and engineering teams to create bespoke, technology-driven solutions. Integrate Generative AI techniques into the ML platform using cutting-edge methods. Required Qualifications, Capabilities, and Skills: Formal academic training or certification (Master’s or PhD) in Computer Science, Machine Learning, or a related discipline, with hands-on experience in applied ML. Proficiency in at least … learning and deep learning techniques. Expert-level knowledge of deep learning frameworks like PyTorch or TensorFlow. Experience in advanced ML areas including GPU optimisation, fine-tuning, embedding models, inference, prompt engineering, evaluation, and Retrieval-Augmented Generation (RAG). Ability to independently manage and complete tasks and projects with minimal supervision. High attention to detail, strong follow-through, excellent More ❯

experiments using the latest ML technologies; analyse results and fine-tune models. Write production-level code in Python, transforming experimental outcomes into real-world applications by closely collaborating with engineering teams. Take ownership of end-to-end development for both proof-of-concept work and production-ready solutions. Improve system accuracy and efficiency by identifying performance issues and removing … bottlenecks. Partner with product and engineering teams to create bespoke, technology-driven solutions. Integrate Generative AI techniques into the ML platform using cutting-edge methods. Required Qualifications, Capabilities, and Skills: Formal academic training or certification (Master’s or PhD) in Computer Science, Machine Learning, or a related discipline, with hands-on experience in applied ML. Proficiency in at least … learning and deep learning techniques. Expert-level knowledge of deep learning frameworks like PyTorch or TensorFlow. Experience in advanced ML areas including GPU optimisation, fine-tuning, embedding models, inference, prompt engineering, evaluation, and Retrieval-Augmented Generation (RAG). Ability to independently manage and complete tasks and projects with minimal supervision. High attention to detail, strong follow-through, excellent More ❯

services . Here's how you'll contribute: You'll do this by: Lead the architecture, design, and development of large-scale, distributed systems. Work closely with product and engineering teams to define architecture blueprints and technology roadmaps. Develop high-level and low-level design documents. Be hands-on with coding in Java (latest versions) and guide teams on … Select appropriate AWS services and design cloud-native architectures with cost, scalability, and security in mind. Conduct design and code reviews to ensure quality and performance. Mentor and guide engineering teams on architectural decisions and technical challenges. Stay updated with new Java features, AWS services, and emerging architectural trends. Core Skills: Required Skills & Qualifications ~15 years of software development … enterprise applications to enhance user experience, decision-making, and automation. Exposure to modern AI application patterns such as: Retrieval-Augmented Generation (RAG) for augmenting LLMs with domain-specific knowledge. Prompt engineering and fine-tuning for tailoring model behavior to business-specific contexts. Use of embedding stores and vector databases (e.g., Pinecone, Redis, Azure AI Search) to support semantic More ❯

services . Here's how you'll contribute: You'll do this by: Lead the architecture, design, and development of large-scale, distributed systems. Work closely with product and engineering teams to define architecture blueprints and technology roadmaps. Develop high-level and low-level design documents. Be hands-on with coding in Java (latest versions) and guide teams on … Select appropriate AWS services and design cloud-native architectures with cost, scalability, and security in mind. Conduct design and code reviews to ensure quality and performance. Mentor and guide engineering teams on architectural decisions and technical challenges. Stay updated with new Java features, AWS services, and emerging architectural trends. Core Skills: Required Skills & Qualifications ~15 years of software development … enterprise applications to enhance user experience, decision-making, and automation. Exposure to modern AI application patterns such as: Retrieval-Augmented Generation (RAG) for augmenting LLMs with domain-specific knowledge. Prompt engineering and fine-tuning for tailoring model behavior to business-specific contexts. Use of embedding stores and vector databases (e.g., Pinecone, Redis, Azure AI Search) to support semantic More ❯

design, develop, and maintain cutting-edge LLM-based agentic applications. This role requires hands-on expertise in frameworks such as LangChain or LangGraph (or comparable frameworks), and techniques including prompt engineering, Retrieval-Augmented Generation (RAG), and fine-tuning. In other words, you will be expected to ship deliverables yourself too. You will build solutions to meet functional requirements … analytics. Keep track of latest research: Given that this is a fast evolving field, it’s important to keep track of the latest advancements in fine-tuning, RLHF, and prompt engineering advancements such as DSPy. System Design & Architecture: Translate high-level product requirements into scalable, modular software designs that adhere to modern design principles, microservices architecture, and cloud More ❯

and asset behaviour analytics Conduct advanced experimentation and model development, applying deep learning, LLMs, or probabilistic methods as appropriate Build high-performance, production-grade pipelines for data ingestion, feature engineering, model training, and real-time inference Develop and maintain robust APIs and infrastructure for scalable model deployment, monitoring, and versioning Apply rigorous model evaluation, performance tuning, and A/… in machine learning, including supervised/unsupervised learning, NLP, and/or deep learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP) Excellent problem-solving skills and a passion … for innovation and continuous learning Strong Python programming skills to write clean, modular code and experience with core data science libraries Solid software engineering practices: version control, modular design, unit/integration testing, CI/CD pipelines Comfortable working with both structured and unstructured data; experience writing with SQL queries To be a successful Insurwaver, your attitude is as More ❯

and asset behaviour analytics Conduct advanced experimentation and model development, applying deep learning, LLMs, or probabilistic methods as appropriate Build high-performance, production-grade pipelines for data ingestion, feature engineering, model training, and real-time inference Develop and maintain robust APIs and infrastructure for scalable model deployment, monitoring, and versioning Apply rigorous model evaluation, performance tuning, and A/… in machine learning, including supervised/unsupervised learning, NLP, and/or deep learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP) Excellent problem-solving skills and a passion … for innovation and continuous learning Strong Python programming skills to write clean, modular code and experience with core data science libraries Solid software engineering practices: version control, modular design, unit/integration testing, CI/CD pipelines Comfortable working with both structured and unstructured data; experience writing with SQL queries To be a successful Insurwaver, your attitude is as More ❯

Stay ahead of market trends in Generative AI, Responsible AI, and emerging AI use cases across sectors. Advise internal stakeholders on how evolving technologies (e.g. vector databases, RAG pipelines, prompt engineering) can drive value in future proposals. Qualifications Experience & Skills Proven experience in pre-sales or client-facing architecture roles involving AI, data science, or analytics. Strong ability More ❯

Stay ahead of market trends in Generative AI, Responsible AI, and emerging AI use cases across sectors. Advise internal stakeholders on how evolving technologies (e.g. vector databases, RAG pipelines, prompt engineering) can drive value in future proposals. Qualifications Experience & Skills Proven experience in pre-sales or client-facing architecture roles involving AI, data science, or analytics. Strong ability More ❯

Stay ahead of market trends in Generative AI, Responsible AI, and emerging AI use cases across sectors. Advise internal stakeholders on how evolving technologies (e.g. vector databases, RAG pipelines, prompt engineering) can drive value in future proposals. Qualifications Experience & Skills Proven experience in pre-sales or client-facing architecture roles involving AI, data science, or analytics. Strong ability More ❯

developrec Head of Global Delivery Centre | Tech Recruitment Partner @ developrec AI Engineer – Agentic Systems & Automation – £70,000 – Fully remote in UK A fast-growing company at the forefront of engineering innovation and AI automation is seeking an experienced AI Engineer to help develop intelligent, scalable agentic systems integrated into modern software development lifecycles. This role involves leading the design … and deployment of LLM-powered agents, developer tools, and automation frameworks that streamline workflows and elevate productivity. This is a hands-on engineering role that blends software development, AI experimentation, and product innovation. The successful candidate will play a key role in architecting agent-based systems, leveraging advanced frameworks such as LangChain and LlamaIndex, and deploying real-time AI … frameworks like LangChain, LangGraph, and LlamaIndex to enhance developer workflows. Tooling & Assistant Innovation: Develop AI-powered assistants and developer tools with an emphasis on scalability, performance, and reliability. AI Engineering: Build, test, and optimize generative AI features using platforms such as OpenAI, Claude, and Gemini, including fine-tuned custom models and evaluation pipelines. Prompt Engineering: Design, iterate More ❯

To build and run a data platform which can create and deliver analytics to colleagues and deliver regulatory reporting Ingest and transform data from multiple systems, modelling data and engineering data marts to create reusable data assets To create a self service BI platform, enabling colleagues across Rentokil Initial to get value from data To build AI models and … a data science platform that enables Rentokil to derive huge value from AI, through machine learning to gen AI and beyond Key tasks: AI Data Engineering: Design, build, operate, and deploy real-time data pipelines at scale using AI techniques and best practices. Support Rentokil's AI R&D efforts by applying advanced data warehousing, data science, and data … engineering technologies. Aim for automation to enable a faster time-to-market and better reusability of new AI initiatives. Collaboration: Work in tandem with the AI team to collect, create, curate, and maintain high-quality AI datasets. Ensure alignment of data architecture and data models across different products and platforms. Hands-on Involvement: Engage in data engineering tasks More ❯

Bell Canada, MasMovil, Telenor, HP, KPMG, and more. About the Position AI Engineers are responsible for developing and integrating AI solutions into Hiya's products, focusing on rapid iteration, prompt engineering, and practical application. You'll fine-tune and optimize foundation models, craft sophisticated multi-agent systems, and invent novel solutions to power the next generation of voice … You'll Do Integrate AI solutions into existing products and workflows Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions Conduct model evaluations, prompt engineering, and fine-tuning of large language models (LLMs) Implement and manage AI orchestration, including agent-based systems Participate in the design and implementation of AI-powered applications … fast start if you have experience: Experience with cloud platforms such as AWS, Google Cloud, or Azure Knowledge of Kubernetes and containerization technologies Experience with data science and ML engineering Familiarity with retrieval-augmented generation (RAG) The requirements listed in the job descriptions are guidelines. You don't have to satisfy every requirement or meet every qualification listed. If More ❯