Top Tech Jobs & Startup Jobs in London

Design and industrialize production-grade AI and LLM platforms for ASOS. Build RAG systems, fine-tuned models, agentic workflows, orchestration layers, evaluation frameworks, vector retrieval pipelines, and AI safety guardrails on Azure. Develop reusable capabilities that scale across teams, optimize performance, cost, and reliability, and partner with security stakeholders on governance and responsible AI.

Manage a portfolio of partner fashion brands on ASOS, driving sales growth, trading performance, assortment optimization, availability, and customer experience. Build strategic relationships, lead business reviews, analyze commercial metrics, identify opportunities, coordinate seasonal initiatives, support partner onboarding, and collaborate with internal teams across merchandising, trade, operations, and product.

Build and lead scalable data engineering solutions supporting machine learning, analytics, pricing, forecasting, customer value, marketing, and personalization initiatives. The role involves developing Python, Spark, Databricks, and cloud-based data pipelines; designing data architectures and models; improving data quality and observability; operationalizing machine learning models; optimizing performance and costs; and mentoring engineers while partnering with technical and business stakeholders.

Manages ASOS’s business continuity, disaster recovery, crisis management, operational resilience, and Group Insurance programs. Responsibilities include developing BCDR frameworks, coordinating impact assessments and testing, managing insurance renewals and claims, overseeing broker and insurer relationships, advising stakeholders on risk and controls, leading a Senior Risk Analyst, and supporting incident response, governance, training, and resilience improvements across the business.

Lead the architecture and production delivery of large-scale machine learning systems for personalized recommendations, search relevance, outfit discovery, and AI Stylist experiences. Set technical direction across ML platforms, ranking, retrieval, deep learning, generative AI, and MLOps. Partner with scientists, engineers, product managers, and senior stakeholders; drive scalable, reliable systems; mentor senior engineers; and establish engineering standards across teams.

Senior Legal Counsel providing broad commercial legal advice across supply chain, marketing, consumer regulation, technology, payments, and ecommerce matters. Responsibilities include drafting and negotiating contracts, advising on cross-border compliance and regulatory issues, managing disputes and complaints, supporting technology initiatives, overseeing external counsel, managing junior lawyers, and implementing legal processes and training.

Supports Topshop’s design team across trend research, mood boards, CAD development, technical sketches, design packs, samples, fittings, fit notes, range reviews, and product sign-offs. The role contributes creative ideas while maintaining design archives and seasonal inspiration libraries. It requires a recent fashion design degree, strong Adobe Creative Suite skills, fashion and trend awareness, organization, collaboration, communication, and a creative portfolio.

Leads integrated annual and seasonal brand planning across global and local markets. Translates brand strategy into executable plans, communications models, channel roles, calendars, governance, investment principles, and measurable outcomes. Coordinates cross-functional stakeholders, agencies, market teams, and execution partners while overseeing reporting and effectiveness insights. Maintains planning rhythms, resolves dependencies, supports decision-making, improves planning processes, and coaches analysts to connect performance learning with future brand plans.

Own and evolve ASOS’s data warehouse, ERP-to-warehouse synchronization, data pipelines, reconciliations, and Power BI reporting. Mentor BI engineers, set technical standards, prioritize team delivery, and build complex solutions using Python, PySpark, Delta Lake, Databricks, Azure, SQL, and dimensional modeling. Partner with Finance, Commercial, Buying, Product, Architecture, Security, and Risk stakeholders while improving platform cost, performance, reliability, governance, and data quality. Support a potential migration from Databricks to Microsoft Fabric.

Build and scale shared AI platform capabilities on Azure, with emphasis on agentic AI runtimes, orchestration, tool integration, LLMOps, evaluation, observability, security, and reliability. Develop reusable templates, standards, and reference implementations for enterprise AI adoption. Partner with product, infrastructure, security, and engineering teams to establish governed model access, lifecycle management, CI/CD, and production-ready AI operating practices.