Top AWS Jobs in London

Drive growth by partnering with sales teams, demonstrating product value, managing customer relationships, and ensuring successful implementations in cybersecurity.

Lead and deliver AI-native customer experiences by designing frontend-to-orchestration architectures, prototyping LLM-driven interfaces, mentoring engineers, running POCs, advising clients on AI transformation, and operationalizing RAG, vector storage, agentic systems, and AI observability.

Lead technical onboarding of enterprise clients across Europe: map client data and business rules, design ingestion and integration layers, handle localisation and regulatory complexity, document reusable patterns, feed product feedback, and use LLM tooling to accelerate integration.

Architect, design and deliver production-grade AI solutions using ML, generative and agentic AI. Lead technical delivery, implement RAG/prompt engineering, ensure responsible AI, drive cloud-native, scalable architectures, mentor and manage junior engineers, and collaborate with clients to translate business needs.

Lead Data & AI strategy engagements for public-sector and regulated clients: assess maturity, prioritise use cases, build business and investment cases, design transformation roadmaps, advise on technology strategy, and support sales, delivery and capability building. Act as trusted advisor to senior stakeholders and mentor consultants to move clients from experimentation to scaled delivery.

Design and document market-data workflows, integrations, and data pipelines for risk analytics. Translate business needs into specifications, data mappings, user stories, and test plans. Investigate data issues using SQL/Python, support UAT and releases, and improve controls, monitoring, automation, and operational processes across Market Data and Integration.

Lead service transition and IT project delivery from implementation to operational handover. Manage scope, timelines, risks, change requests, budgets, governance and operational readiness. Coordinate cross-functional teams, suppliers and stakeholders, ensure Service Desk and support teams are trained for go-live, contribute to bids/RFPs, and drive continuous improvement of transition and project practices.

As an Engineering Manager, you will lead high-performing teams, mentor engineers, set engineering best practices, and ensure rapid project delivery while collaborating cross-functionally.

Develop and maintain front-end and back-end AI-enabled web and desktop applications. Collaborate with cross-functional teams to design features, optimize scalability and security, troubleshoot defects, participate in code reviews, and implement AI assistant technology integrated with enterprise systems.

Lead go-to-market and new logo growth in assigned verticals, craft industry-specific value propositions for data collaboration and clean room solutions, engage senior stakeholders across legal/compliance/data strategy, and close enterprise deals while advising on identity resolution and privacy regulation compliance.

Build and deploy commercial data science models for churn prediction, cross-sell and upsell, revenue attribution, and next-best-action recommendations. Design experiments and causal analyses, productionize models on AWS, manage feature engineering and monitoring, and communicate insights to Sales, Marketing, Customer Success, Finance, and executive stakeholders. The role requires strong Python, SQL, statistics, cloud data warehouse, and production machine learning experience.

Design and build Python services, pipelines, testing frameworks, data analysis tools, and lifecycle management systems for quantitative market and credit risk models. Implement auditable AI/ML and LLM-based automation for documentation, data quality, testing, and workflow assistance. Collaborate with quants, validators, data engineers, and program leaders while promoting secure engineering practices, mentoring developers, and contributing to technical design.

Maintains, supports, enhances, and leads the lifecycle management of critical IP network infrastructure. Responsibilities include fault resolution, planned maintenance, network upgrades, project delivery, service transition, testing, documentation, supplier supervision, network design updates, continuous improvement, and technical mentoring. The role requires expertise in complex always-on networks, routing protocols, MPLS, multicast, Cisco platforms, QoS, data center technologies, security devices, AWS, and automation.

Design, develop, and support scalable backend services, APIs, cloud-native microservices, and distributed event-driven systems for banking and financial services. Drive architecture, coding standards, testing, automation, operational resilience, security, and compliance. Support production systems and incident management while collaborating with engineering, product, architecture, and business teams. Mentor engineers, influence technical practices, and balance long-term architecture with delivery priorities.

Lead and grow a team of Data Scientists, Data Engineers, and ML Ops Engineers developing large-scale autonomy data pipelines and machine learning solutions for perception and planning. Define technical direction, data strategy, evaluation frameworks, and production processes. Guide data collection, curation, labeling, sampling, model deployment, and optimization while ensuring scalability, cost efficiency, safety, and quality. Collaborate globally across infrastructure, simulation, tooling, and autonomy teams.

Build practical AI-powered applications, internal tools, workflow automations, and platform features. Integrate LLMs, APIs, services, databases, and business data across cloud-based systems. Develop, test, monitor, debug, document, and improve production-ready software while collaborating with engineering, product, operations, and business stakeholders. Apply prompt engineering, retrieval workflows, and responsible AI practices to solve operational problems.

Develop and execute Algolia’s DACH partner strategy across Germany, Austria, and Switzerland. Manage consulting, systems integration, technology, and cloud partner relationships; recruit and enable new partners; shape AI and agentic solutions; coordinate co-selling, co-marketing, deal registration, and account mapping; and drive pipeline, revenue, and customer wins. The role requires strong technical fluency, German and English fluency, Salesforce experience, strategic relationship management, and cross-functional leadership.

Lead transformative AWS initiatives, shaping solutions across financial services, advising on strategy, and designing cloud architectures while mentoring teams.

Design, develop, maintain, and review software for critical infrastructure. Contribute to feature design, product roadmaps, Agile task breakdown, CI/CD pipelines, deployments, and customer demonstrations. Provide technical leadership by guiding engineers through delivery and technical challenges while supporting backend or frontend development across cloud, containerization, and database technologies.

Develop and scale Android mobile applications using Kotlin, contribute to backend services, and support mobile network management, MDM, and AI-powered safeguarding systems. The role involves architecture, security, scalability, rapid product iteration, deployment, pilot testing, and direct collaboration with the CTO and product team. The engineer will own features end to end, engage with users, and deliver technology that protects children and vulnerable people.

Develop and maintain iOS mobile applications and frontend experiences while contributing to backend services powering mobile network management, device control, and AI-driven safeguarding. Collaborate on architecture, scalability, security, and product direction; deploy, optimize, test, and rapidly iterate features across care, schools, and parent products. Engage directly with users and take ownership from concept through production delivery.

Build and scale Voop’s full-stack platform across real-time web applications, iOS and Android mobile apps, backend services, mobile network management, device control, and AI-driven safeguarding tools. The role involves architectural decisions, frontend and backend development, AWS deployment, optimization, security, real-world testing, and close collaboration with the CTO. Engineers will own features end to end and engage with users to deliver measurable safeguarding impact.

Senior Software Engineer responsible for designing, building, and operating secure, scalable AWS serverless applications using MongoDB. The role owns end-to-end software delivery, architecture, testing, code reviews, technical debt reduction, operational excellence, and continuous improvement. It also involves mentoring engineers, influencing technical direction, collaborating with stakeholders, and applying Agile practices, secure development, clean architecture, and customer-focused engineering principles.

Owns deployment, operations, reliability, and productionization of a centralized enterprise AI-SDLC platform. Responsibilities include infrastructure management, CI/CD automation, monitoring, observability, incident response, security and governance controls, multi-tenant scalability, cost management, and operational support. The role uses cloud, containers, infrastructure as code, scripting, and reliability engineering practices, with preferred experience in LLMOps, MLOps, model hosting, API gateways, and AI platform management.

Leads complex security engineering initiatives, establishes technical strategy and architecture, develops security roadmaps, and embeds security-by-design across cloud, distributed, microservices, and AI-enabled environments. Acts as a security subject matter expert, mentors engineers, evaluates new security capabilities, and supports complex cyber incident and vulnerability response. Requires broad information security expertise, strong stakeholder influence, cloud experience, and technical leadership.