126 to 150 of 282 Prompt Engineering Jobs in London

Prompt Engineer (Claude/Claude Code) - Mortgage Sales £695 per day Outside IR35 Ideally London 1 day per week/Can be fully remote A leading UK mortgage technology provider is looking for a Prompt Engineer with strong Claude and Claude Code experience to support the development … making sure the requirements, prompts and AI outputs are right. What you'll need: Strong hands-on experience with Claude and Claude Code Prompt engineering experience, including prompt design and optimisation Excellent requirements gathering and stakeholder engagement skills The ability to understand business processes and translate them ...

support our clients transition to a sustainable future. Role Summary This is an exciting opportunity to join the expanding AI & Innovation team within Architecture & Engineering function at a key stage in SMBC EMEA's AI journey. The team plays a central role in shaping and delivering AI strategy, governance … control alignment and production readiness activities. Ensure all solutions align with AI Policy, AI Standard, security, data privacy and regulatory requirements Work closely with engineering and delivery teams to ensure solution designs are effectively implemented and meet intended outcomes. Provide hands-on support in prototyping, validation and troubleshooting where ...

systems integrating multi-modal LLMs (text, image, audio, video), design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG, optimise and deploy large language and multi-modal models with a focus on performance and latency and build scalable MLOps pipelines … applications to support robust, production-grade AI deployments. Using a consultative approach you'll guide multidisciplinary teams and clients through strategic decisions in AI engineering and GenAI adoption. About you: You have achieved a 2.1 or above bachelor's degree in Computer Science, AI or related STEM disciplines ...

tooling, or extending platform logic. Collaborate closely with cross‐functional teams internally and with customers to ensure solution success. Provide structured feedback to Platform Engineering and Product on feature gaps and customer pain points. Contribute to technical best practices and accelerate solution delivery through reusable assets, frameworks, and documentation. … broader landscape of Enterprise & Agentic AI. Qualifications Undergraduate, master’s degree or Phd in Computer Science or Data Science. 4+ years of experience in engineering, with 2+ years in customer‐facing or field roles. Proven success building and deploying AI/ML or data‐intensive applications in production. Deep ...

Overview The Applied Innovation (of AI) Engineering team is an elite machine learning group strategically located within the Chief Data Analytics Office (CDAO) Technology group of JPMorgan Chase. AI Engineering tackles business critical priorities using innovative machine learning techniques and technologies with a focus on machine learning … Software, Cybersecurity and Technology Infrastructure. The team partners closely with all lines of business and engineering teams across the firm to execute long-term projects in these areas that require significant machine learning development to support JPMorgan Chase businesses as they grow. Responsibilities Collaborates with engineers, data scientists ...

them, and become the technical voice Yuno trusts on how to build AI agents responsibly at scale. Skills You Need Minimum Qualifications Extensive software engineering experience, with a track record building and shipping production LLM or AI‐agent systems. Deep expertise in agentic systems — multi‐step agents, tool … orchestration, memory, and retrieval‐augmented generation (RAG). Strong LLM application skills — prompt engineering, evaluation, and guardrails for reliable, safe outputs. Strong Python for AI/ML, plus solid backend engineering (Go and/or Kotlin) to productionize systems at scale. Model serving and LLM inference, with ...

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 … 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 ...

task at hand whilst considering cost implications and timelines. If you have a curiosity and passion for AI, whilst a firm grounding in software engineering principles enabling you to build industry leading products, we'd love to hear from you! Proficiency in at least one programming language. I.e Python … APIs etc) Experience in building and optimising systems for performance, scalability, and reliability Understanding of ML fundamentals (training, evaluation, deployment) and LLM‐specific challenges (prompt engineering, latency, cost optimisation, hallucinations, evaluation) Experience with cloud platforms (AWS, GCP, Azure) and infrastructure‐as‐code (Terraform etc). Hands‐on with ...

Financial Services Tax practice, helping banks, insurers and asset managers reinvent how their tax and finance functions operate. We combine data engineering, intelligent automation and artificial intelligence – from AI-ready data foundations to generative and agentic AI – to transform tax compliance, reporting and advisory. As a Senior Manager … 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 ...

tooling, or extending platform logic. Collaborate closely with cross-functional teams internally and with customers to ensure solution success. Provide structured feedback to Platform Engineering and Product on feature gaps and customer pain points. Contribute to technical best practices and accelerate solution delivery through reusable assets, frameworks, and documentation. … broader landscape of Enterprise & Agentic AI. Qualifications Undergraduate, master's degree or Phd in Computer Science or Data Science 4+ years of experience in engineering, with 2+ years in customer-facing or field roles. Proven success building and deploying AI/ML or data-intensive applications in production. Deep ...

evaluation frameworks, fine-tune foundation models, build custom AI models and create automated feedback loops to continuously improve performance. You'll work closely with engineering and product teams to deliver robust AI solutions that solve real-world compliance challenges. The ideal candidate will have experience within AI research … engineering, including hands-on work with LLMs, model fine-tuning and agentic systems. Experience with computer vision, model evaluation frameworks and MLOps practices would be highly beneficial. This is an excellent opportunity for someone who thrives in a fast-paced environment and wants to work on genuinely impactful ...

data scientists and data engineers, you'll help move AI from experimentation into secure, scalable products that deliver real business value. This is an engineering role with genuine ownership. You'll be involved throughout the AI lifecycle, from designing and deploying solutions through to monitoring, optimisation and governance. … working with technologies including Azure Databricks, Azure Machine Learning, Azure AI Foundry, LangChain, LangGraph and Python, building enterprise AI applications using RAG, vector databases, prompt orchestration and tool‐calling patterns. You’ll need experience with: Deploying LLMs and machine learning models into Azure enterprise environments. Azure Databricks, Azure Machine ...

across teams. You will design and own production‐grade implementations, from architecture through deployment and iteration. You will contribute to shared libraries such as prompt libraries and skills to improve discoverability and consistency for business users. You will help deliver measurable commercial impact while meeting firm resilience, controls … Payments domain. Knowledge of financial services with exposure to Payments and or Banking workflows. Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related quantitative field. Demonstrated experience partnering with non‐technical business stakeholders to scope, build, and ship technical solutions. Hands‐on experience writing ...

propose better patterns, and own the implementation quality of your workstream from first commit through production cutover. This role blends deep Amazon Connect platform engineering, generative AI development on Bedrock and Claude, and full-stack serverless work, with regular direct interaction with customer engineering teams. Responsibilities Your Assignment … validate it with turn-by-turn trace analysis Optimize inference cost and latency hands-on: model tier selection (Haiku vs. Sonnet vs. Opus), prompt caching, and token budgeting against containment-rate targets Diagnose AI agent performance using observability tooling (agent spans, and CloudWatch) that correlates contact flow logs, conversation ...

opportunity to impact your career and help you push the limits of what is possible. You will help teams adopt approved AI-assisted engineering practices that improve quality, speed, and operational resilience. If you enjoy building practical agentic tools and setting strong engineering standards, you will find meaningful … ownership and growth here. As an Applied AI ML Lead Engineer, Vice President in the Applied AI and Machine Learning engineering team within Asset and Wealth Management, you will enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will ...

across teams. You will design and own production-grade implementations, from architecture through deployment and iteration. You will contribute to shared libraries such as prompt libraries and skills to improve discoverability and consistency for business users. You will help deliver measurable commercial impact while meeting firm resilience, controls … Payments domain. Knowledge of financial services with exposure to Payments and or Banking workflows. Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field. Demonstrated experience partnering with non-technical business stakeholders to scope, build, and ship technical solutions. Hands-on experience writing ...

scalable, secure, and aligned with RELX Responsible AI standards. This is a senior individual‐contributor role with broad influence. You will partner closely with Engineering Leads, Product Managers, Data Scientists, and data teams within LNIP. Key Responsibilities Define and own the AI architecture vision for Protégé in PatentSight+, ensuring … patterns for AI‐driven enrichment and classification of patent data at scale, ensuring results are dependable, auditable, and consistent with established IP metrics. Establish prompt engineering standards, evaluation harnesses, and quality frameworks to govern LLM behaviour and maintain output accuracy in production. Partner with Product Management to assess ...

capacity as the scope of AI at 9fin accelerates. Backed by over $170M in funding (Series C), we are scaling rapidly across product, engineering, and go-to-market. AI is not a bolt-on feature at 9fin; it is the core differentiator for the next phase of the company. … management experience, preferably in FinTech or B2B SaaS, with at least 2 years focused on ML or GenAI productsWorking knowledge of RAG architectures, embeddings, prompt engineering, and LLM evaluation methods (not just "AI concepts" at a high level)Experience shipping AI products where output quality is probabilistic ...

opportunity to impact your career and help you push the limits of what is possible. You will help teams adopt approved AI-assisted engineering practices that improve quality, speed, and operational resilience. If you enjoy building practical agentic tools and setting strong engineering standards, you will find meaningful … ownership and growth here. As an Applied AI ML Lead Engineer, Vice President in the Applied AI and Machine Learning engineering team within Asset and Wealth Management, you will enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will ...

opportunity to impact your career and help you push the limits of what is possible. You will help teams adopt approved AI-assisted engineering practices that improve quality, speed, and operational resilience. If you enjoy building practical agentic tools and setting strong engineering standards, you will find meaningful … ownership and growth here. As an Applied AI ML Lead Engineer, Vice President in the Applied AI and Machine Learning engineering team within Asset and Wealth Management, you will enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will ...

opportunity to impact your career and help you push the limits of what is possible. You will help teams adopt approved AI-assisted engineering practices that improve quality, speed, and operational resilience. If you enjoy building practical agentic tools and setting strong engineering standards, you will find meaningful … ownership and growth here. As an Applied AI ML Lead Engineer, Vice President in the Applied AI and Machine Learning engineering team within Asset and Wealth Management, you will enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will ...

opportunity to impact your career and help you push the limits of what is possible. You will help teams adopt approved AI-assisted engineering practices that improve quality, speed, and operational resilience. If you enjoy building practical agentic tools and setting strong engineering standards, you will find meaningful … ownership and growth here. As an Applied AI ML Lead Engineer, Vice President in the Applied AI and Machine Learning engineering team within Asset and Wealth Management, you will enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will ...

using Copilot Studio (Full), Power Platform, Dynamics 365, and Azure AI; establish security, governance, and performance baselines. Design and implement LLM-powered solutions (RAG, prompt engineering, grounded generation) with data governance, telemetry, and quality monitoring ( LLMOps ). Integrate Microsoft 365 and Dynamics 365 with enterprise systems and APIs … implementations; guide fit‐gap analysis and oversee deployments. Champion Copilot Agent security & governance (role‐based access, data loss controls, audit/observability). Mentor engineering teams and contribute to accelerators, reference architectures, and best practices; support RPA/Desktop Flows when required. Required Skills & Competencies Consulting Core Structured communication ...

their production SaaS platform, build the next generation of AI-powered capabilities, and work directly with the founders to shape both the product and engineering function as the business scales. The Role Own a production, multi-tenant SaaS platform used by enterprise customers. Design, build and scale full-stack … Next.js, Go, Python and AWS. Build AI-powered features, LLM integrations, agentic workflows and automation tools. Work directly with founders to influence product strategy, engineering direction and future hiring. Develop cloud-native systems using AWS Serverless, Lambda, PostgreSQL, Supabase and modern API architectures. Improve platform reliability, observability, security, performance ...

experience building voice agents, vision systems, or conversational AI serving real users Strong LLM foundations hands-on with modern foundation models including fine-tuning, prompt engineering, and evaluation methodologies Agent framework proficiency production experience with LangChain, LlamaIndex, or similar orchestration frameworks Voice AI platform experience built real-time … explain complex AI concepts clearly to both technical and business stakeholders Customer-facing experience in Solutions Architecture, Technical Account Management, or Pre-Sales Engineering is highly desirable Computer vision experience working with video processing, object detection, or vision-language models is a plus Model fine-tuning practical experience with ...