Top Tech Jobs & Startup Jobs in London

Designs inclusive, user-centred digital products and public services for government and private-sector clients. Responsibilities include content and interaction design, user research, prototyping, usability testing, workshop facilitation, stakeholder engagement, and evidence-based service improvement. The role also contributes to agile multidisciplinary delivery, design practice development, mentoring, proposals, and thought leadership. Experience with UK Government digital services, GOV.UK standards, WCAG, Figma, and the GOV.UK Prototype Kit is required.

Designs, develops, tests, implements, and supports .NET applications and integrations using C#, ASP.NET, APIs, and SQL Server. Works directly with clients to translate business requirements into secure, maintainable solutions. The role also delivers Microsoft 365 and Power Platform solutions, VBA automation, Word macros, and Crystal Reports. Responsibilities include troubleshooting, architecture, code reviews, documentation, knowledge transfer, and managing multiple projects or workstreams.

Design, build, and deploy scalable AI architectures, pipelines, LLM integrations, RAG systems, and multi-agent workflows. Operationalize generative AI and NLP solutions in production, collaborate with data engineers on infrastructure and vector databases, and champion AI-assisted coding practices. Provide technical consulting to clients, mentor teams, and advise on AI product development, modern data stacks, synthetic data, and explainable AI.

Conduct performance and non-functional testing across API, front-end, and UI applications. Gather requirements, review non-functional requirements, develop and maintain test scripts, execute tests, analyze results, identify failures and risks, and communicate findings to technical, business, client, and third-party stakeholders. The role includes performance testing against Azure infrastructure and managing multiple client projects.

Conduct business and systems analysis across digital product delivery projects. Responsibilities include mapping business processes and journeys, defining technical and non-functional requirements, maintaining traceability, writing user stories and acceptance criteria, supporting Agile ceremonies and testing, and facilitating stakeholder workshops. The role bridges business, product, architecture, engineering, and delivery teams while using data to validate assumptions and measure outcomes.

Design, develop, deploy, and monitor machine learning and AI models, including predictive models, NLP, computer vision, and generative AI solutions. Analyze and transform large datasets, build scalable data pipelines, automate ML workflows, evaluate model performance, and integrate models into production. Collaborate with technical and business stakeholders to deliver actionable insights and continuously improve AI products.

Define product vision and strategy, manage roadmaps and backlogs, prioritize features, and guide digital product delivery. Collaborate with clients, stakeholders, designers, developers, researchers, business analysts, and delivery teams. Use customer feedback, analytics, and research to make evidence-based decisions, establish success measures, lead Agile ceremonies, manage trade-offs, and drive continuous product improvement.

Develop and maintain Python applications, services, data processing solutions, and scalable ETL/ELT pipelines. Integrate structured and unstructured data from APIs, databases, files, and streaming systems while ensuring quality, performance, reliability, and security. Collaborate with engineering and architecture teams, contribute to data platform design, implement testing and monitoring, and support technical documentation and engineering standards.

As a Full Stack Engineer, you will handle the full development lifecycle, engage with stakeholders, and promote best practices in engineering.

Design, build, and maintain high-performance Java backend systems that integrate and deploy AI/ML models. Develop RESTful microservices, optimize performance and security, implement CI/CD, work with cloud platforms and container orchestration, and collaborate with data scientists on scalable ML solutions.