Top Tech Jobs & Startup Jobs in London

Owns the architecture and delivery of ASOS’s internal Developer Experience platform, including Backstage, golden paths, engineering metrics, DORA instrumentation, and AI-assisted tooling. Designs scalable platform features, establishes engineering standards, mentors engineers, and shapes technical direction. Integrates GitHub Copilot, MCP servers, and other agentic AI workflows while evaluating their effectiveness and safety. Collaborates with platform, security, infrastructure, and product engineering teams to improve onboarding, developer productivity, and service delivery.

Manage a portfolio of brand partnerships for ASOS Media Group, serving as the primary commercial and marketing contact. Develop retail media proposals, grow advertising revenue, identify upsell opportunities, and present strategic recommendations. Collaborate with buying, retail, marketing, creative, production, ad operations, and insights teams to deliver campaigns. Advise brands on digital advertising, audience targeting, measurement, and emerging retail media opportunities.

Lead product vision, strategy, and roadmaps for ASOS’s enterprise transformation from Oracle to Microsoft Dynamics. Simplify complex operational processes, develop scalable capabilities, and apply AI, automation, and agentic workflows across supplier onboarding, inventory, fulfillment, and partner operations. Collaborate with Engineering, Data, Finance, Operations, Commercial, and senior stakeholders to prioritize initiatives, drive measurable outcomes, support organizational change, and coach product managers.

Monitors endpoints, triages alerts, investigates malware and suspicious activity, supports incident response and root-cause analysis, and conducts threat hunting. The role improves detection through alert tuning, prioritization, automation, documentation, and process development. It also serves as a security subject matter expert, supports major incidents, coaches colleagues, contributes to security culture, and participates in a one-week-in-five on-call rota.

Assists the Leisure Menswear Designer in researching trends, developing fashion-forward ranges, selecting colors and fabrics, and designing commercial products. Collaborates with technical teams, buyers, suppliers, and factories on product construction, fits, materials, and trims. Uses sales data to inform designs, manages critical path deadlines, supports supplier relationships, and reacts quickly to emerging trends for global ASOS customers.

Designs and develops ASOS DESIGN menswear ranges through trend research, shape and color development, fabric and trim selection, block development, and commercial range planning. Collaborates with buying, merchandising, technical teams, suppliers, and factories to deliver fashion-forward products on schedule. Uses sales insights to guide product decisions, manages critical paths and PLM processes, supports fittings and problem solving, and communicates departmental performance and strategy.

Leads the SOC and Incident Response team, directing security monitoring, detection engineering, incident investigations, threat-led analysis, and post-incident improvement. Oversees analysts and the external MSSP, develops response processes, tunes detections, manages incident metrics, conducts training and simulations, and communicates cyber risks and performance to senior stakeholders. Requires hands-on expertise across SIEM, EDR, cloud, identity, email security, and forensic tooling.

Designs, deploys, and operates production machine learning systems for customer engagement, marketing, pricing, personalization, and commercial decision-making. Owns data ingestion, feature engineering, deployment, monitoring, optimization, and MLOps infrastructure. Partners with Applied Scientists, Data Engineers, and ML Engineers to productionize research, build scalable tooling, influence architecture, improve reliability, and mentor engineers.

Design, build, deploy, and operate large-scale batch and real-time machine learning systems for search, ranking, recommendations, and personalization. Collaborate with applied scientists, engineers, and product managers to deliver measurable customer impact. Improve engineering practices, contribute to technical direction, and mentor other engineers across the machine learning community.

Design, build, deploy, and operate production machine learning systems for personalized recommendations, outfit discovery, retrieval, ranking, and generative AI experiences. Partner with scientists, engineers, and product managers to optimize deep learning models serving millions of customers. Improve scalability, reliability, observability, and performance while contributing to architecture, shared ML capabilities, engineering practices, and mentoring.