1 to 25 of 528 Prompt Engineering Jobs in the UK

with estimations and technical input. Interacting with clients to understand their business challenges, goals, and requirements. Skills, Knowledge and Expertise Education & Qualifications: Bachelor's degree in Computer Science, Software Engineering, Maths, Physics or related field. Degree in Data Science, AI, Statistics desirable but not essential. Experience: 2+ years' commercial experience (including internships or placement year) developing Data or AI … and communication skills. Growth mindset, curiosity, and ability to quickly learn new services. Understanding of data warehousing concepts, star/snowflake schemas, and DAX. Basic knowledge of MLOps or prompt engineering for generative AI. Benefits Are you ready to join the Data & AI Apps team at Nasstar? • AI is in our DNA - We live and breathe AI. It More ❯

record of managing the end-to-end product lifecycle-from ideation through launch and optimization-preferably in complex, matrixed organizations Strong understanding of GenAI concepts, including LLMs, AI agents, prompt engineering, and platform capabilities (e.g., Azure AI Foundry, Google Vertex AI) Experience working with cross-functional teams, including engineering, data science, design, and business stakeholders Demonstrated ability More ❯

record of managing the end-to-end product lifecycle-from ideation through launch and optimization-preferably in complex, matrixed organizations Strong understanding of GenAI concepts, including LLMs, AI agents, prompt engineering, and platform capabilities (e.g., Azure AI Foundry, Google Vertex AI) Experience working with cross-functional teams, including engineering, data science, design, and business stakeholders Demonstrated ability More ❯

record of managing the end-to-end product lifecycle-from ideation through launch and optimization-preferably in complex, matrixed organizations Strong understanding of GenAI concepts, including LLMs, AI agents, prompt engineering, and platform capabilities (e.g., Azure AI Foundry, Google Vertex AI) Experience working with cross-functional teams, including engineering, data science, design, and business stakeholders Demonstrated ability More ❯

delivery. We’re not only shaping the future of AI in business — we’re shaping the future of talent. This role is ideal for someone passionate about advanced AI engineering today and curious about evolving into a product leadership role tomorrow. You'll get exposure to customer discovery, roadmap planning, and strategic decision-making alongside your technical contributions. Role … in the research, development, and deployment of next-generation GenAI and machine learning solutions . Your scope will go beyond retrieval-augmented generation (RAG) to include areas such as prompt engineering, long-context LLM orchestration, multi-modal model integration (voice, text, image, PDF), and agent-based workflows. You will help assess trade-offs between RAG and context-native … strategies, explore hybrid techniques, and build intelligent pipelines that blend structured and unstructured data. You’ll work with technologies such as LLMs, vector databases, orchestration frameworks, prompt chaining libraries, and embedding models, embedding intelligence into complex, business-critical systems. This role sits at the intersection of rapid GenAI prototyping and rigorous enterprise deployment, giving you hands-on influence over More ❯

developing and integrating cutting-edge AI solutions—including LLMs and AI agents —into our products and operations at a leading SaaS company. You’ll collaborate closely with product and engineering teams to deliver innovative, high-impact systems that push the boundaries of AI in rebate management. This is a highly collaborative and fast-moving environment where your contributions will … or in collaboration with other specialists. Optimize model pipelines for latency, scalability, and cost-efficiency, and support real-time and batch inference needs. Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration. Stay informed on current research and emerging tools in LLMs, generative AI, and autonomous agents, and evaluate their practical applicability. … Participate in roadmap planning, design reviews, and documentation to ensure robust and maintainable systems. Required Qualifications 5+ years of experience in machine learning engineering, applied AI, or related fields. Bachelor’s or Master’s degree in Computer Science, Machine Learning, Engineering, or a related technical discipline. Strong foundation in machine learning and data science fundamentals—including supervised/ More ❯

and share knowledge with broader technology teams Mentors junior team members in AI/ML technologies and approaches Required qualifications, capabilities and skills Formal training or certification on software engineering concepts and applied experience with focus on AI/ML applications Hands-on experience with Large Language Models (GPT, BERT, etc.) Strong understanding of Generative AI concepts and applications … Proficiency in prompt engineering techniques Advanced Python programming skills Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face) Familiarity with cloud-based AI services (AWS, Azure, or GCP) Knowledge of software engineering best practices including Git, CI/CD, and testing Overall knowledge of the Software Development Life Cycle Strong communication skills to explain complex technical concepts Demonstrated More ❯

at delivering across the full product lifecycle. About the Job: As a member of the Capco Technology Delivery Team, you'll bring practical knowledge of agile development methodologies and engineering best practices. As an AI Engineer, you'll play an integral role using your experience and skills to contribute to the quality and implementation of our projects. What You … text, image, audio, and video) to support complex, real-world tasks Create robust agentic workflows enabling AI agents to interact autonomously with data sources and external APIs using advanced prompt engineering and retrieval-augmented generation (RAG) Fine-tune and optimize pre-trained large language models and multi-modal models for targeted use cases, ensuring high performance and low … latency in production. Implement distributed training and scalable MLOps pipelines for continuous model improvement Collaborate with cross-functional teams-research, product, and engineering-to embed AI capabilities into products and services Evaluate and select appropriate AI frameworks (e.g., LangChain, LlamaIndex) to integrate agent components seamlessly with enterprise systems Build full-stack applications (front-end interfaces and back-end APIs More ❯

core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build … and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions. Optimizes system accuracy and performance by identifying and resolving … inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrates Generative AI within the ML Platform using state-of-the-art techniques. Required qualifications, capabilities, and skills MS and/or PhD in Computer Science, Machine Learning, or a related field, with applied machine learning experience. Experience in one of the More ❯

core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build … and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions. Optimizes system accuracy and performance by identifying and resolving … inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrates Generative AI within the ML Platform using state-of-the-art techniques. Required qualifications, capabilities, and skills MS and/or PhD in Computer Science, Machine Learning, or a related field, with applied machine learning experience. Experience in one of the More ❯

core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build … and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions. Optimizes system accuracy and performance by identifying and resolving … inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrates Generative AI within the ML Platform using state-of-the-art techniques. Required Qualifications, Capabilities, And Skills MS and/or PhD in Computer Science, Machine Learning, or a related field, with applied machine learning experience. Experience in one of the More ❯

developing and integrating cutting-edge AI solutions-including LLMs and AI agents -into our products and operations at a leading SaaS company. You'll collaborate closely with product and engineering teams to deliver innovative, high-impact systems that push the boundaries of AI in rebate management. This is a highly collaborative and fast-moving environment where your contributions will … or in collaboration with other specialists. Optimize model pipelines for latency, scalability, and cost-efficiency , and support real-time and batch inference needs. Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration. Stay informed on current research and emerging tools in LLMs, generative AI, and autonomous agents , and evaluate their practical applicability. … Participate in roadmap planning, design reviews, and documentation to ensure robust and maintainable systems. Required Qualifications 5+ years of experience in machine learning engineering, applied AI, or related fields. Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering , or a related technical discipline. Strong foundation in machine learning and data science fundamentals -including supervised/ More ❯

ML team as we scale beyond our seed round. Key Responsibilities 1. Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (eg, neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS … learning models (eg, CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). … Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). Leadership & Communication: Proven ability to lead cross-functional teams in ambiguous startup settings. Exceptional written and verbal communication skills-able to explain complex concepts to both technical and non-technical stakeholders. Experience recruiting and mentoring engineers More ❯

ML team as we scale beyond our seed round. ⸻ Key Responsibilities 1. Architecture & Hands-On Development • Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. • Rapidly prototype novel models (e.g., neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. • Productionize models in cloud/on-prem environments (AWS … learning models (e.g., CNNs, Transformers, graph neural networks) in real-world applications. • Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). • Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). • Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). … Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). • Leadership & Communication: • Proven ability to lead cross-functional teams in ambiguous startup settings. • Exceptional written and verbal communication skills—able to explain complex concepts to both technical and non-technical stakeholders. • Experience recruiting and mentoring engineers More ❯

/ML team as we scale beyond our seed round. ⸻ Key Responsibilities Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (e.g., neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS … learning models (e.g., CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). … Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). Leadership & Communication: Proven ability to lead cross-functional teams in ambiguous startup settings. Exceptional written and verbal communication skills—able to explain complex concepts to both technical and non-technical stakeholders. Experience recruiting and mentoring engineers More ❯

core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build … and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions. Optimizes system accuracy and performance by identifying and resolving … inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrates Generative AI within the ML Platform using state-of-the-art techniques. Required qualifications, capabilities, and skills Formal training or certification (MS and/or PhD) in Computer Science, Machine Learning, or a related field, with applied machine learning concepts experience. More ❯

core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build … and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions. Optimizes system accuracy and performance by identifying and resolving … inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrates Generative AI within the ML Platform using state-of-the-art techniques. Required qualifications, capabilities, and skills Formal training or certification (MS and/or PhD) in Computer Science, Machine Learning, or a related field, with applied machine learning concepts experience. More ❯

etc Annual Leave 23 days rising to 27 with length of service Sick Pay Increasing with length of service The Role: Senior AI Engineer Overview of role AI Data Engineering: Design, build, operate, and deploy real-time data pipelines at scale using AI techniques and best practices. Support 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 Product Owner and other team members to create, curate, and maintain high-quality AI assets. Ensure alignment of data architecture and data models across different products and platforms. Hands-on Involvement … Engage in data engineering tasks as required to support the team and the projects. Conduct and own external data collection efforts - including state-of-the-art prompt engineering techniques to support the construction of state-of-the-art AI models. Stay up-to-date with new technologies and best practices in data engineering, advancements in generative More ❯

core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build … proficiency in large models (LLMs) and related techniques. Conduct experiments using the latest ML technologies, analyze results, and tune models. Implement experimental results into production solutions by collaborating with engineering teams, including hands-on coding in Python for proof of concept/experimentation and production-ready solutions. Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks … collaborating with product and engineering teams to deliver tailored solutions. Integrate Generative AI within the ML Platform using state-of-the-art techniques. Required Qualifications, Capabilities, and Skills MS and/or PhD in Computer Science, Machine Learning, or a related field, with applied machine learning experience. Experience in programming languages such as Python, Java, C/C++, etc. More ❯

promptly if you are a good match for this role due to high levels of interest. We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As an AI/ML Python Engineer at JPMorgan Chase within the Client Onboarding and KYC Engineering team, your responsibilities will include probing … Conduct ad-hoc and periodic analysis as required by business stakeholders, the model risk function, and other groups. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience. Experience in statistical inference and experimental design (such as probability, linear algebra, calculus). Data wrangling: understanding complex datasets, cleaning, reshaping, and joining messy … pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG). Experience in anomaly detection techniques, algorithms, and applications. Excellent problem-solving, communication (verbal and written), and More ❯

core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build … techniques. Enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques. Conduct experiments using the latest ML technologies, analyze results, and tune models. Collaborate with engineering teams to bring experimental results into production solutions, owning end-to-end code development in Python for proof of concept, experimentation, and production-ready solutions. Optimize system accuracy and … performance by identifying and resolving inefficiencies and bottlenecks, collaborating with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrate Generative AI within the ML Platform using state-of-the-art techniques. Required qualifications, capabilities, and skills MS and/or PhD in Computer Science, Machine Learning, or a related field, with applied machine learning experience. 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 ❯

machine learning principles. Experience in rapid prototyping on large datasets. Building autonomous workflows using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, including prompt engineering and LLMs. Proficiency in Python, Docker, and version control with Git. Knowledge of Databricks. Excellent communication skills for conveying complex concepts. Experience working in Agile environments. Ability More ❯

learning principles. Proficiency in rapid prototyping on large datasets. Experience with frameworks like Langchain, Semantic Kernel, AutoGen, LangGraph for agentic workflows. Expertise in developing and optimizing generative AI models, prompt engineering, and LLMs. Strong Python development skills, including Docker and version control with Git. Knowledge of Databricks. Excellent communication skills for conveying complex concepts. Experience in Agile environments More ❯