Top Engineering Jobs in London

Build and ship AI-powered product capabilities for enterprise IT operations. Design production systems involving LLMs, agents, RAG, vector search, knowledge graphs, workflow orchestration, APIs, integrations, and automation. Own features from customer discovery through implementation, launch, troubleshooting, and iteration. Collaborate directly with customers and cross-functional teams while making pragmatic tradeoffs around reliability, cost, latency, and scalability.

Lead and develop a hands-on engineering team building Azure-based revenue management SaaS. Responsibilities include coding, code review, architecture, technical standards, roadmap delivery, hiring, performance management, career development, and cross-functional collaboration. The manager owns team commitments, delivery quality, continuous improvement, and engineering alignment with business goals while applying AI-augmented development practices.

Support the delivery, rollout, adoption, and continuous improvement of AI-powered products. Translate user and operational needs into requirements, user stories, acceptance criteria, and delivery plans; coordinate with engineering, QA, UX, and business teams; manage feedback and issue triage; support UAT, training, releases, dashboards, adoption tracking, and data-driven workflow improvements.

Lead the architecture and development of an AI-powered Production Intelligence platform combining SRE, observability, agentic AI, and automated remediation. Build AI agents, MCP integrations, telemetry pipelines, anomaly detection, evaluation frameworks, and safe human-in-the-loop workflows. Define reliability practices including SLIs, SLOs, error budgets, incident response, and post-incident reviews. Mentor engineers, establish technical standards, and coordinate delivery across global application and infrastructure teams.

Build and maintain investment data solutions, quantitative models, performance attribution systems, dashboards, and reporting workflows. Validate data quality, automate analytical processes, support backtesting and scenario analysis, apply model governance, and collaborate with investment, technology, and risk teams. The role also evaluates emerging technologies, including artificial intelligence and machine learning, to improve investment research and decision-making.

Build and maintain investment data solutions, quantitative models, performance attribution systems, dashboards, and automated reporting workflows. Partner with investment, technology, and risk teams to support portfolio construction, research, manager selection, and investment oversight. Responsibilities include validating data, improving data quality, applying model governance, conducting quantitative analysis, and evaluating emerging technologies such as artificial intelligence and machine learning.

Lead and develop a product engineering squad, balancing people leadership, delivery accountability, and technical guidance. Responsibilities include recruiting, coaching, planning, delivery health, production readiness, system reliability, security, scalability, and maintainability. Partner with product managers and engineering leaders to align priorities, guide technical decisions, improve delivery predictability, and support responsible use of AI-assisted engineering tools.

Build and maintain backend AI capabilities for GitLab Duo Chat: design flow components and agentic flows in Python/LangGraph, integrate LLMs and multi-agent orchestration, implement and maintain APIs in the Rails monolith, improve observability and reliability, and participate in on-call rotations and cross-functional collaboration to deliver safe, scalable AI chat features.

Lead pre- and post-sales technical efforts as a subject matter expert in application security and AI-native development. Create solution architectures, support large deals, unblock technical issues, influence product strategy with field feedback, deliver technical presentations to diverse audiences, and mentor the global Solutions Engineering community.

Leads an engineering team while remaining technically engaged through code reviews, pairing, and high-impact contributions. Sets direction, converts ambiguity into delivery plans, and partners with Product, Design, and Operations. Improves code quality, observability, incident response, analytics, and developer velocity. Owns hiring, coaching, feedback, performance management, and team growth in a fast-paced startup environment.

Leads the technology strategy, architecture, delivery, and evolution of ClearBank’s UK payments capabilities. Oversees engineering teams, ensures scalable, resilient, secure, and operationally ready services, and partners with Product to shape long-term roadmaps. Guides build-versus-buy decisions, third-party integrations, regulatory controls, stakeholder communication, and team development within a regulated banking environment.

Manage engineering and building maintenance services at Brettenham House, supporting mechanical, electrical, and public health systems. The role operates Monday through Friday from 08:00 to 17:00 and includes a one-in-two callout rota. Responsibilities are not detailed in the posting and require contacting the recruitment team for further information.

Architect-level hands-on leader for iOS and Android mobile platforms. Own end-to-end mobile architecture, drive technical standards, contribute to core code, lead testing/CI/CD, observability, release processes, and mentor engineers while partnering with product, design, backend, security, and QA.

Lead an agile engineering team to design, build, review, and maintain secure, high-quality production software. Provide technical direction, drive product and architecture decisions, champion firmwide SDLC practices and AI-assisted engineering, and ensure operational stability and reusable automation across cloud-native applications.

Own the full sales cycle for mid-market customers, from prospecting and discovery through negotiation and close. Build pipeline among engineering, hardware, aerospace, and defense organizations; manage high-volume opportunities; partner with product and engineering; represent Flow at industry events; and help refine positioning, pricing, and go-to-market strategy.

Leads a multidisciplinary engineering organization responsible for enterprise-scale data and AI infrastructure. Owns the data platform technical roadmap, cloud architecture, governance, security posture, FinOps, vendor relationships, and modernization programs. Provides architectural oversight, mentors engineers and architects, manages delivery planning, and aligns technical solutions with commercial and business goals. Requires extensive cloud data platform, data engineering, application development, governance, security, CI/CD, and stakeholder management experience.

Leads the Review Tooling engineering team building investigation, enforcement, analytics, privacy-preserving, and sandbox platforms. Defines the product vision and roadmap, scales human review through Claude-assisted automation, partners with policy, operations, legal, privacy, and data science teams, and ensures reliable systems align with data retention commitments. Responsible for hiring, coaching, technical strategy, stakeholder communication, and engineering-wide initiatives.

Lead Supabase’s Billing engineering team, overseeing people management, hiring, roadmap delivery, technical direction, partnerships, and incident response. Own systems covering subscriptions, usage-based billing, invoices, payments, taxation, entitlements, collections, and provider integrations. Build a healthy remote team, ensure predictable delivery, improve reliability and operational maturity, and coordinate with Product, Finance, Data, Support, Sales, and Partnerships on revenue-critical initiatives.

Provides hands-on manual, exploratory, regression, and risk-based QA for Salesforce and web tickets. Extends existing AIO automation and evaluates additional tools to improve coverage and maintainability. The role collaborates with the QA lead, engineering, and Business Systems teams to prioritize commercially significant risks, strengthen QA processes, support release decisions, and report quality metrics. This is a 4–6 month fixed-term hybrid contract.

Leads a multidisciplinary engineering organization responsible for enterprise data and AI infrastructure. Owns data platform architecture, technical roadmaps, governance, security, cloud cost optimization, vendor relationships, and modernization programs. Provides architectural guidance, mentors engineers, oversees migrations and integrations, and aligns product and engineering delivery with business goals. Requires strong expertise in cloud data platforms, data modeling, pipelines, application development, visualization, security, CI/CD, and AI/ML integration.

Leads geographically dispersed customer solutions and professional services teams, overseeing solutioning, project delivery, engineering, and operations. Ensures customer engagements are delivered on time, within budget, and at high quality while managing resources, methodologies, profitability, escalations, and continuous improvement. Builds team capability, coaches leaders, standardizes global practices, supports customer training, and partners with business units on customer requirements and product enhancements.

Lead and develop a software engineering team responsible for scalable backend services, APIs, data processing, and production operations. Own delivery across the software lifecycle, establish quality and reliability practices, partner with Product and AI/ML teams, manage priorities and risks, coach engineers, recruit talent, and build an inclusive culture. The role requires strong backend, cloud, distributed systems, CI/CD, observability, and people leadership experience.

Manage and coach a distributed team of Support Engineers operating 24/7. Co-own support KPIs, quality, processes, triage, escalations, incidents, and post-mortems. Remain technically hands-on by troubleshooting APIs, SDKs, and logs. Partner with Product and Engineering leadership, communicate performance, identify training needs, and improve operational excellence across customer support.

Lead and grow a distributed team of engineers building Spotify’s experimentation SaaS platform. Responsibilities include hiring, coaching, career development, delivery quality, product prioritization, technical strategy, collaboration with product managers and Staff Engineers, and occasional hands-on engineering. The role is based in Stockholm with hybrid flexibility.

Leads multidisciplinary engineering squads delivering large-scale banking technology programs. Responsibilities include setting engineering strategy, guiding cloud-native and microservices architecture, owning end-to-end delivery, enforcing quality and security standards, driving DevOps and operational excellence, managing stakeholders and risks, and developing distributed engineering teams. The role also oversees governance, release readiness, technical debt reduction, platform modernization, regulatory compliance, and production stability across strategic banking initiatives.