Lead Software Engineer - Python, Trading

Job responsibilities

• Acts as the primary technology leader in India for X Commodities Workflows, owning delivery commitments, prioritization, and execution plans in partnership with global desk/product stakeholders.
• Partners with Sales/Trading and Functional leads to identify workflow pain points, define user journeys and acceptance criteria, and deliver solutions that improve speed, clarity, and controls.
• Drives features from concept to production across the SDLC—requirements, design, build, automated testing (unit/integration/contract), release, and ongoing support.
• Ensures solutions meet front-office expectations for usability, resilience, performance, auditability, and operational robustness . Leads implementation of workflow orchestration across core ecosystems and partner platforms (booking, pricing, positions, risk, P&L, reporting), ensuring strong contract discipline (API/event/data) and integration alignment.
• Coordinates dependencies across multiple global teams to deliver clean releases , manage cutovers, and reduce integration risk. Stay hands-on where needed: design reviews, critical-path coding, debugging production issues, and leading incident resolution with strong root-cause discipline.
• Drives engineering standards: code quality, secure coding, test strategy, CI/CD hygiene, and observability.
• Uses AI tooling to accelerate delivery by converting desk requirements into executable workflow specs (e.g., BDD-style scenarios), UI/API/event/data contracts, integration mappings, and automated tests.
• Keeps documentation living and traceable from requirement to release, enabling faster change with lower operational risk. Builds and mentor a high-performing India team: coaching, hiring, performance management, and career development.
• Establishes strong operating rhythms across time zones (planning, execution tracking, release readiness, on-call/support readiness).
• Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets .