Top Engineering Jobs in London

Lead a large backend engineering team owning the Contacts domain: design scalable distributed systems, improve reliability and security, define product roadmap with PM, mentor engineers, and ensure fast, robust APIs and integrations for both consumer and enterprise customers.

Develop and maintain scalable cloud ecosystems using Golang and Python, enhancing backend microservices and collaborating within a fast-paced team.

Lead and scale Customer Success Engineering across EMEA and APAC: hire and coach CSEs, partner with Sales for account prioritization, run operational cadences and KPI tracking, drive adoption and expansion, surface product feedback, and ensure measurable customer outcomes.

Lead and develop a team of ~8-10 software engineers, owning delivery, career growth, architecture decisions, and roadmap planning with Product. Drive recruitment, performance reviews, processes for scalable, highly available features, and promote AI-augmented development workflows to improve efficiency and product outcomes.

Lead and develop a team of Forward Deployed Engineers to execute customer onboarding, on-site deployments, troubleshooting, and sustained adoption of the Hivemind SDK. Drive field feedback into product, translate mission goals into technical milestones, and partner with engineering and product teams to improve deployment readiness and customer outcomes.

Lead a team building backend systems for business expense management (receipts, expense reports, bookkeeping, card products). Own the technical roadmap, drive architecture and implementation, mentor engineers, collaborate with product and cross-functional squads, and apply LLM technologies to automate document scanning, categorization, and reconciliation.

As the People Enablement Partner, you will lead recruitment for Engineering and Product roles, build talent pipelines, partner with leadership on hiring strategy, and implement performance management frameworks.

Lead and mentor a team of software engineers, overseeing the implementation and optimization of enterprise systems while driving digital transformation initiatives. Collaborate with stakeholders to enhance system efficiency and ensure quality delivery.

Lead a team building shared infrastructure across web, iOS, and Android. Drive technical direction, prioritisation, team development, roadmap strategy, and cross-functional delivery for platform initiatives like monitoring, SDLC improvements, and notifications while balancing short-term delivery and long-term sustainability.

Lead and mentor a cross-functional platform engineering team building verification (KYC) platform rails. Own technical roadmap, ensure reliability, scalability and operational excellence, collaborate with global stakeholders, contribute hands-on to delivery, run on-call and incident response, and drive platform integrations, review tooling and versioned configuration-driven rules.

Manage and grow an Endpoint engineering team to build and scale backend infrastructure that ingests, aggregates, and stores agent-collected telemetry. Collaborate with product and cross-functional teams to deliver assurance use cases, drive data processing and availability at scale, and support engineers' career development.

Manage and coach a regional Sales Engineering team to qualify and close opportunities. Lead technical customer engagements, support demos and POCs, recruit and onboard talent, collaborate with Product, Support, and Enablement, and run performance reviews and development plans.

The Engineering Manager will lead a Data Replay & Recovery Team to build a data replay application, improve service efficiency, and design a data platform for processing large datasets.

Lead and scale EMEA sales engineering: build and develop SE leaders, own technical pre-sales strategy, drive technical excellence across the sales cycle, engage CxOs on architecture and cyber resilience, and partner cross-functionally to align enablement, hiring, and field intelligence.

Lead data engineering teams to design and deliver reusable data pipelines and architectures across businesses. Set governance, coding standards, and AI-assisted workflow controls; influence stakeholders, manage resources, hire and develop talent, and ensure secure, auditable, and resilient solutions.

Lead design, development, testing, and operation of ultra-low-latency C++ trading and risk modules, integrating FPGA acceleration. Drive latency optimization, CI/CD, AI-assisted engineering adoption, automation, and cross-team collaboration to ensure reliability and performance.

Lead design, build, and maintain large-scale, secure data engineering solutions. Produce and review production code, improve operational stability, drive AI-assisted engineering adoption, evaluate vendors, and shape technical strategy and team culture.

Lead technical design, develop secure cloud-native applications, drive adoption of enterprise-authorized AI-assisted engineering, improve automation and operational stability, evaluate vendors, and promote engineering excellence across teams.

Lead frontend engineer responsible for designing and delivering cloud-native, mobile-first solutions. Collaborate with cross-functional teams, write clean/testable code, troubleshoot, mentor junior developers, adopt AI-assisted development practices, and drive continuous improvement of development processes and automation.

Lead design, develop, and optimize low-latency options algorithmic trading systems. Produce high-quality Java code, implement order management, market data processing, and risk systems. Drive automation, CI/CD, performance tuning, and adoption of enterprise AI-assisted engineering practices. Ensure operational stability, testing, and collaboration with product and trading teams.

Lead design and delivery of high-performance, real-time data pipelines and analytics for trading. Drive AI-enabled data engineering, mentor engineers, manage global initiatives, and improve SDLC, testing, and operational reliability.

Lead design and delivery of production-grade AI/ML and agentic solutions for the LLM Suite platform. Own architecture, implementation, and operational stability using public cloud services and agentic frameworks. Build GenAI services, integrate LLMs, ensure secure high-quality code, and improve platform scalability and reliability through collaboration and communities of practice.

Lead design, development, and performance tuning of ultra-low-latency C++ trading systems for equity derivatives market making. Define technology roadmap, drive cross-regional platform delivery, mentor engineers, engage trading desks and quants to translate requirements, promote engineering best practices and CI tooling, and build/scale the EMEA engineering team through hiring pipelines and university partnerships.

Design, build, and maintain production-grade AI/ML and agentic systems for the LLM Suite. Write secure, high-quality code, integrate models and services on public cloud (Azure/AWS), collaborate on design and operational reliability, and operationalize agentic patterns like A2A communication and Model Context Protocol.

Lead design and delivery of enterprise-grade ML systems and production architectures. Build scalable, distributed, data-intensive applications using MLOps and cloud infrastructure (AWS, Kubernetes). Translate research into deployable ML solutions, implement automated pipelines, leverage PyTorch/NumPy and higher-level interfaces, collaborate with SRE/cloud teams, and mentor or optionally manage team members.