Top Tech Jobs & Startup Jobs in London

Supports the Consumer Duty and conduct risk framework for an international consumer business. Responsibilities include assessing customer-impact risks, conducting thematic reviews, analyzing complaints and management information, developing conduct metrics, preparing governance materials, tracking remediation, supporting audits and regulatory requests, and promoting customer-outcome improvements through data, automation, and AI.

Leads software engineering for JPMorganChase Markets Technology, owning technical components across design, coding, quality, stability, scalability, compliance, and security. Partners with business and engineering teams, drives architecture and technical decisions, develops and reviews production Java code, resolves stakeholder conflicts, and leads complex initiatives across applications and workflows. Promotes enterprise engineering standards, responsible AI-assisted development, and secure cloud platform practices.

Supports prime finance trading desks with trade bookings, execution oversight, exception and workflow management, query resolution, and control completion. Acts as a liaison between trading desks, operations, technology, product, vendors, and other stakeholders. The role requires strong analytical, numerical, communication, problem-solving, governance, and process-improvement skills, with a focus on streamlining workflows and improving operational efficiency.

Analyze and structure infrastructure, renewable energy, transportation, and green technology financing transactions. Build financial models, assess credit and portfolio risks, review contracts and financial statements, recommend loan structures and risk ratings, prepare credit memoranda, and support approvals and transaction execution. Manage existing portfolios by reviewing amendments, monitoring covenants, limits, ratings, industry trends, and counterparty exposure while collaborating with banking, financing, and markets teams.

Analyze AI adoption, portfolio, benefits, engagement, and cost data to produce executive-ready insights and recommendations. Build scalable Python workflows, dashboards, visualizations, and automation integrating multiple data sources. Improve reporting accuracy, lineage, reproducibility, standardization, and near-real-time visibility while partnering with stakeholders to deliver analytics capabilities and operating model improvements.

Lead onboarding and running equities client billing to the strategic cost & commission calculator. Own monthly billing cycle, transform manual processes into scalable automated solutions, embed controls and documentation, partner with front office, technology, operations and risk, and present progress and metrics to global stakeholders.

Lead an ML engineering team building and operating scalable AI, ML, and LLM solutions for financial-crimes monitoring. Responsibilities include developing risk features and data pipelines in Databricks, productionizing supervised and unsupervised models, monitoring drift and bias, improving explainability and auditability, and collaborating with product, SRE, compliance, and data science teams.

Leads Risk Technology’s Ways of Working transformation and broader capability-building portfolio. Develops technology program plans, manages resources, budgets, risks, dependencies, and stakeholders, and drives agile delivery. Scales AI-assisted engineering and governance practices across a large organization, defines delivery and adoption metrics, and advises senior leadership on efficiency, investment, operating models, and control frameworks.

Advises JPMorgan’s EMEA futures, options, and cleared derivatives business on complex documentation, clearing structures, margin, collateral, segregation, default scenarios, legal opinions, and regulatory issues. Drafts and negotiates client agreements, give-up documentation, and cleared OTC derivatives contracts; coordinates approvals and escalations; engages clients and counsel; assesses risks; and mentors junior lawyers.

Develop AI/ML-driven analytics, automation, data architectures, and sequential decision-making tools for Securities Services. Responsibilities span data processing, quantitative modeling, prototype-to-production development, balance-sheet and deposit optimization, visualization, and stakeholder presentations. The role collaborates with Quantitative Research, Technology, and data teams to solve complex commercial problems using machine learning, large language models, and cloud or HPC environments.