51 to 75 of 512 Prompt Engineering Jobs in the UK

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 ❯

of AI innovation, combining cutting-edge techniques with unique data assets to optimise business decisions and automate processes. This role offers a unique blend of scientific research and software engineering, allowing you to advance AI in financial services and build impactful products. In this role, you will leverage the latest research in Natural Language Processing and statistical machine learning … to build AI-powered products that automate processes and enhance decision-making. You will collaborate with software engineering teams to design scalable Machine Learning services and communicate AI capabilities to diverse audiences. Job Responsibilities: Lead the development and implementation of advanced machine learning models and algorithms to address complex operational challenges. Architect and oversee the deployment of generative AI … APIs (e.g., OpenAI) and open source (e.g., Huggingface). Experience with integrating user feedback to establish data flywheels and self-improving AI applications. Solid understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms (AWS). Excellent problem-solving skills and the ability to work independently and collaboratively. Strong communication skills to effectively convey complex More ❯

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 … 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. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying AI models in cloud computing environments (AWS, Azure, Google Cloud). Deep … understanding of enterprise AI architecture, data engineering, and model optimization . Strong problem-solving skills, with a business-driven approach to AI implementation. Effective communication and collaboration skills in cross-functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms More ❯

new skills and experiences that will propel your career to new heights. Making animals' lives better makes life better - join our team today! Location: UK, Hook (Hybrid) Team: Software Engineering & Platforms Supervisor: IT Engineering Director Career Progression: Engineering, Architecture, Analyst Over the past 4 years Elanco IT has been on an incredibly exciting journey. Separating from our … opportunity to build a modern technology stack free of the burden of large-scale technical debt. We are now looking to take this one step further, leveraging newly established engineering capabilities to help Elanco deliver on customer needs faster than ever before. This role is part of our new enterprise platform engineering team with a specific focus on … implementations in Elanco. This is an incredibly exciting opportunity to not only work on cutting edge technology but to contribute to the continued growth of a new highly skilled engineering organization. To be successful in an engineering role in Elanco requires a highly motivated individual, with an innovative mindset and a willingness to drive tangible outcomes. The individual More ❯

in Romania is playing a crucial role in driving the evolution of CFO Solution Platform, propelling us forward as a market leader. These hires will augment our existing Software Engineering teams to support the development of our AI capabilities. As an Principal/Senior AI Software Engineer, you will utilise your technical knowledge to build our AI Core foundation … OOP languages (backend development) Proficient in Python programming with experience in AI/ML libraries such as LangChain, PydanticAI, NumPy Expertise in Large Language Models (LLMs) including fine-tuning, prompt engineering, and working daily with models like GPT, Claude, Gemini Hands-on experience with vector databases (e.g., OpenSearch, FAISS) for efficient similarity search and semantic search & retrieval of More ❯

graph-based AI to solve business challenges. You will interact with customer stakeholders to manage project scope, priorities, deliverables, risks and issues, and timelines for successful customer outcomes. Solution Engineering: You will develop, test, and deploy production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks. This involves writing production-level code, optimizing for performance and … in designing and developing enterprise-class applications, demonstrating a strong understanding of software development lifecycle principles. LLM Proficiency : 2+ years of Experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, and integrating LLMs into applications. Maintain up-to-date knowledge of different LLM providers and their strengths and limitations (e.g., OpenAI's GPT and O … including AI orchestration frameworks (e.g., LangChain, Llama Index, Haystack) and cloud provider AI offerings (e.g., AWS Bedrock, Vertex AI, Azure Machine Learning). Data Expertise : Strong foundation in data engineering, data analytics, or data science, with the ability to work effectively with various data types and sources. Experience using big data technologies (e.g. Hadoop, Spark, Hive) and database management More ❯

of LLM-based applications. · Strong experience with Python and orchestration libraries such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or similar. · Deep knowledge of LLMs (GPT, Claude, LLaMA, Mistral, etc.), prompt engineering, agent memory, tool calling, and autonomous task execution. · Experience with RFP/RFI support, and proposal creation in a consulting or enterprise services environment. · Understanding of enterprise More ❯

of LLM-based applications. • Strong experience with Python and orchestration libraries such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or similar. • Deep knowledge of LLMs (GPT, Claude, LLaMA, Mistral, etc.), prompt engineering, agent memory, tool calling, and autonomous task execution. • Experience with RFP/RFI support, and proposal creation in a consulting or enterprise services environment. • Understanding of enterprise More ❯

or life sciences environment Deep understanding of the clinical trial lifecycle and operations (e.g., clinical operations, site monitoring). Strong technical fluency in AI/ML concepts, including, LLMs, prompt engineering, and agent orchestration Demonstrated ability to lead cross-functional teams and deliver products in regulated envioronments Excellend communication and stakeholder management skills Bonus Points: Advanced degree in More ❯

or life sciences environment Deep understanding of the clinical trial lifecycle and operations (e.g., clinical operations, site monitoring). Strong technical fluency in AI/ML concepts, including, LLMs, prompt engineering, and agent orchestration Demonstrated ability to lead cross-functional teams and deliver products in regulated envioronments Excellend communication and stakeholder management skills Bonus Points: Advanced degree in More ❯

month ago Be among the first 25 applicants Direct message the job poster from Morae Senior Director Human Resources | Talent & People We are looking for a Product Engineering Director to lead our engineering organization at the intersection of innovation, performance, and customer-centric delivery. As a senior leader reporting directly to the Chief Product Officer , you will be … secure, and high-performance solutions that transform the way legal professionals work. You will drive the development of our GenAI-enabled products , ensure delivery excellence, and foster a strong engineering culture rooted in agile practices, modern architecture, and continuous innovation. Key Responsibilities: Engineering Strategy & Technical Leadership Own the technical execution of the product roadmap in partnership with the … automation. Drive platform extensibility, scalability, and security for enterprise legal environments. Leverage agentic frameworks to create adaptive and context-aware features that enhance legal workflows. Execution & Delivery Champion agile engineering practices across cross-functional squads. Ensure high-quality, on-time delivery of features with clear metrics and accountability. Manage engineering capacity, prioritization, sprint planning, and release cycles in More ❯

full-time hybrid role , based in the Nottingham area , with regular in-office collaboration. Salary: £60,000 - £75,000 The Role You'll be a key member of the engineering team, focused on building LLM-driven features, intelligent agents , and ML-powered backend systems that automate and optimise intricate workflows. It’s an ideal role for someone with strong … Doing Design, build, and deploy ML-powered features, agents, and APIs to automate unstructured tasks Build production-level backend and microservices in Python and TypeScript Work with product and engineering teams to shape models, services, and system behaviour Contribute to system architecture and infrastructure for scale, observability, and performance Explore and implement LLMs, prompt engineering, and AI … orchestration frameworks Take ownership of features end-to-end, from design to deployment and monitoring What They’re Looking For 5+ years of software engineering experience , with strong ML or backend focus Proficiency in Python and/or TypeScript , and experience with production-grade systems Familiarity with LLMs, AI agents, or orchestration frameworks (OpenAI, Anthropic, LangChain, etc.) Strong grasp More ❯

complex business questions using advanced data and analytics techniques. You’ll be technically proficient in the end-to-end AI and machine learning model development lifecycle, with experience of prompt engineering, and a keen interest in keeping up with the rapidly evolving industry trends. Your role will include working closely with business stakeholders to create hypotheses, design and … evaluate experiments and implement solutions that unlock significant business value in collaboration with teams such as Data Engineering, Machine Learning Operations (MLOps), Architecture, and Software Development. You’ll also proactively identify opportunities, providing the level of advanced analytics support needed for the problem and will provide technical thought leadership regarding the ethical, sustainable and scalable use of AI and … within an Agile framework. Technical Proficiency: You’ll be able to build models and AI Agents in tools such as Microsoft Azure, Data Bricks, Azure Open AI, and using prompt engineering. Collaborative Communication: You’ll possess strong collaboration and communication skills to ensure both technical and non-technical team members understand the cutting-edge solutions. What’s involved: You More ❯

a reality. This is a full-time hybrid role , based in the Nottingham area , with regular in-office collaboration. The Role You'll be a key member of the engineering team, focused on building LLM-driven features, intelligent agents , and ML-powered backend systems that automate and optimise intricate workflows. It’s an ideal role for someone with strong … Doing Design, build, and deploy ML-powered features, agents, and APIs to automate unstructured tasks Build production-level backend and microservices in Python and TypeScript Work with product and engineering teams to shape models, services, and system behaviour Contribute to system architecture and infrastructure for scale, observability, and performance Explore and implement LLMs, prompt engineering, and AI … orchestration frameworks Take ownership of features end-to-end, from design to deployment and monitoring What They’re Looking For 8+ years of software engineering experience , with strong ML or backend focus Proficiency in Python and/or TypeScript , and experience with production-grade systems Familiarity with LLMs, AI agents, or orchestration frameworks (OpenAI, Anthropic, LangChain, etc.) Strong grasp More ❯

a reality. This is a full-time hybrid role , based in the Nottingham area , with regular in-office collaboration. The Role You'll be a key member of the engineering team, focused on building LLM-driven features, intelligent agents , and ML-powered backend systems that automate and optimise intricate workflows. It’s an ideal role for someone with strong … Doing Design, build, and deploy ML-powered features, agents, and APIs to automate unstructured tasks Build production-level backend and microservices in Python and TypeScript Work with product and engineering teams to shape models, services, and system behaviour Contribute to system architecture and infrastructure for scale, observability, and performance Explore and implement LLMs, prompt engineering, and AI … orchestration frameworks Take ownership of features end-to-end, from design to deployment and monitoring What They’re Looking For 8+ years of software engineering experience , with strong ML or backend focus Proficiency in Python and/or TypeScript , and experience with production-grade systems Familiarity with LLMs, AI agents, or orchestration frameworks (OpenAI, Anthropic, LangChain, etc.) Strong grasp More ❯

pension, private medical Our client, a global powerhouse in enterprise IT and AI-led innovation, is looking for a Generative & Agentic AI Engineer to join their high-impact AI engineering team. This role is at the cutting edge of applied LLM development—rapidly prototyping intelligent systems that leverage autonomous agents, reasoning workflows, RAG pipelines, and real-time semantic search. … systems, and semantic search Integrate vector DBs (Pinecone, FAISS, Chroma), cloud AI services, and APIs Develop lightweight UIs (Streamlit, Gradio, React) and observability for demos Work hands-on with prompt engineering, guardrails, and AI safety tools Requirements: Hands-on experinece working with GCP and Google teams Experience with LangChain, LangGraph, CrewAI, Autogen, or similar frameworks Background in RAG … Kingdom 2 weeks ago London, England, United Kingdom 1 week ago Senior Software Engineer – ML Data Platform London, England, United Kingdom 4 days ago Artificial Intelligence/Machine Learning Engineering Lead Greater London, England, United Kingdom 3 weeks ago London, England, United Kingdom 3 weeks ago London, England, United Kingdom 1 week ago London, England, United Kingdom 4 months More ❯

Director, Principal AI/NLP Engineer Introduction to Role: Are you ready to apply your AI/NLP engineering skills in a place where curiosity thrives and groundbreaking work is done? Join our AI Engineering team at AstraZeneca in Cambridge (UK) and be part of a company that follows the science unlike anywhere else! At AstraZeneca, we connect … will develop and deploy NLP models and algorithms to extract insights from unstructured text data. You will design and implement end-to-end NLP pipelines, including data preprocessing, feature engineering, model training, and evaluation. Collaborating with multi-functional teams, you will understand client requirements and develop customized NLP solutions to address their specific needs. By staying up-to-date … and Teamwork: Superior teamwork and communication skills, with a demonstrated ability to mentor and lead teams. - Hands-on Data Expertise: Extensive hands-on experience with data preprocessing techniques, feature engineering, and model evaluation. - Proven Project Delivery: A proven track record of successfully delivering NLP projects in academia or/and industry. - Experience with LLMs and Generative AI: Proficiency in More ❯

and requirements into tasks that can be solved with generative AI, machine learning, or other algorithmic solutions Process structured and unstructured data for generative AI use cases Collaborate with engineering and product development teams Following experimentation and model selection and validation, implement the solution using production-ready Python code Contribute to the full software development lifecycle, including requirements gathering … colleagues and stakeholders Present information using data visualization techniques Qualifications/Requirements: A master’s degree (or equivalent) in a numerate discipline such as Statistics, Machine Learning, Computer Science, Engineering, or Physics. A doctorate is a plus but not required Mid-level professional with 2-4 years of ML/AI experience, typically at an Analyst level role or … external equivalent A scientific approach to solving problems, an analytical mind, and experience in applied machine learning and generative AI Experience in applying LLMs to analyze text documents, prompt engineering, and manual and automatic evaluation of LLM outputs Good foundational knowledge of standard machine learning algorithms and statistical methods Proficient in python and its standard data science and More ❯

pre-sales capacity with the wider account team to demonstrate the impact of Agentforce. In some cases, the use case(s) scope will involve support from the wider Solution Engineering organisation, especially the dedicated Data Cloud and Technical Architect teams. It will also involve collaboration with the new Consumption Lead roles for Data Cloud, the Agentforce Success Engineer role … on the AI landscape and the Salesforce Agentforce, Data Cloud and Platform roadmap. Primary Responsibilities As described above, the role will be responsible for the successful delivery of Solution Engineering led Agentforce Proof of Concepts across the following stages Qualification - working with the SE leadership and account team, you will assist in evaluating POC requests and qualifying their suitability … see and understand the ease of use associated with building agents in Agentforce. This will involve defining Agents, Topic and Actions, including the creation and optimisation of instructions and prompt engineering strategies. This also includes building guardrails to govern the agent behaviour. There is no requirement for detailed documentation but you will be expected to create assets such More ❯

AI solutions end-to-end, from the idea and data exploration phase to deployment and monitoring, balancing cutting-edge techniques with pragmatism to deliver measurable impact. • Apply strong software engineering principles, such as modularity, testing, code reviews, CI/CD and observability, to ensure AI systems are reliable, maintainable, production-ready and can be readily adapted to future developments. … classical ML and NLP techniques, LLM-based solutions, and agentic solutions to balance trade-offs between speed, cost, complexity, interpretability, and performance. • Collaborate closely with product, design, and other engineering teams to scope work, align on success metrics, and incrementally ship improvements in user-facing features powered by AI. • Document system architectures and decision rationale early and clearly, enabling … wide Slack channels, Show and Tell presentations and technical deep-dives. What experience you'll need to be successful • A master's degree or above in Computer Science, Electrical Engineering or a related field. • 5+ years of experience building AI/ML systems in production environments, including ownership of key lifecycle stages: data collection, modeling, evaluation, deployment, and monitoring. More ❯

important will be your expertise in evaluating AI system performance, managing risks, understanding current limitations, and guiding teams on responsible and strategic AI deployment. The role uniquely blends technical engineering with product management responsibilities, supporting our GenAI strategy, and would be a great fit for somebody who loves to empathise with our users to build exciting products that meet … Google ADK, OpenAI's Assistants, litellm, etc (it's not required to know them all), and an understanding of how they facilitate agentic AI development. Strong practical knowledge of prompt engineering techniques and advanced LLM concepts, such as CoT reasoning, prompt chaining, iterative refinement, RAG techniques, MCP, multi-agent architectures, and a clear understanding of when each More ❯

Collaborate over the AI roadmap across GenAI, ML, and Data Science. Lead the AI Centre of Excellence, managing a growing team of AI engineers. Represent AI in senior product, engineering, and vendor forums. Generative AI Delivery Lead design, prototyping, and deployment of GenAI use cases (e.g. co-pilots, AI agents, RAG systems). Establish scalable LLMOps practices including model … evaluation, governance, and lifecycle automation. Maintain awareness of emerging models and integration strategies. Machine Learning Engineering: Support the ML Engineer in model development, deployment, and monitoring. Contribute to pipelines, experimentation design, and MLOps enablement. Provide code and architectural reviews, as well as technical mentoring. Data Science Enablement Act as Data Scientist to support analytics and decision-making needs. Develop … the future structure, tools, and hiring profile for the Data Science function. Required Qualifications: Proven experience building and deploying GenAI applications in production. Strong hands-on knowledge of LLMs, prompt engineering, and retrieval-augmented generation (RAG). Practical experience with traditional ML, including data pipelines and MLOps workflows. Working knowledge of statistical modelling and experimentation. Proficiency in Python More ❯

and optimize vector databases for semantic search across massive intelligence datasets Establish best practices for AI/ML model deployment, monitoring, and continuous improvement Mentor team members on AI engineering practices and drive technical excellence Collaborate with Nisos analysts to understand requirements and translate them into AI-enhanced solutions Own critical platform components from conception through production deployment Who … You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and … Experience mentoring engineers in AI/ML best practices Required and Preferred Education and Experience Degree in Computer Science, AI/ML, or equivalent experience 8+ years of software engineering experience with 3+ years focused on AI/ML systems Proven experience shipping production AI systems at scale Experience in security, intelligence, or OSINT platforms preferred Track record of More ❯

and optimize vector databases for semantic search across massive intelligence datasets Establish best practices for AI/ML model deployment, monitoring, and continuous improvement Mentor team members on AI engineering practices and drive technical excellence Collaborate with Nisos analysts to understand requirements and translate them into AI-enhanced solutions Own critical platform components from conception through production deployment Who … You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and … Experience mentoring engineers in AI/ML best practices Required and Preferred Education and Experience Degree in Computer Science, AI/ML, or equivalent experience 8+ years of software engineering experience with 3+ years focused on AI/ML systems Proven experience shipping production AI systems at scale Experience in security, intelligence, or OSINT platforms preferred Track record of More ❯

and architecture. Ability to thrive and prioritize effectively in a fast-paced, dynamic environment with multiple stakeholders In addition, the following would be an advantage: Hands-on experience with prompt engineering and post-training techniques for large language models, including data pipeline and evaluation methodologies. Experience with ML frameworks such as JAX, PyTorch, or TensorFlow. Experience training and More ❯