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JP Morgan Chase

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Lead Software Engineer - Python, Trading

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Summary

Lead Software Engineer on JPMorganChase's Commodities Systematic Trading desk in Bengaluru, building Python front-office applications that orchestrate the trade lifecycle (execution, booking, pricing, risk/P&L, reporting) within the Athena ecosystem. The role owns delivery for India, mentors a team, and scales AI-assisted engineering practices.

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As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank - Commodities Systematic Trading desk, you work side-by-side with Traders and Functional leads to turn day-to-day desk processes into intuitive, reliable, front-office-grade applications. You will deliver front-to-back workflow solutions that orchestrate the trade lifecycle— execution → booking → pricing → risk/P&L → reporting—partnering across the Athena ecosystem and related platforms to ensure workflows are integrated, controlled, and production ready.

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.

Required qualifications, capabilities, and skills

  • Formal training or certification on Software Engineering concepts and 10+ years applied experience
  • Strong delivery leadership: ability to run multi-stream execution, manage dependencies, and drive outcomes across distributed teams.
  • Python required, otherwise strong engineering background with ability to ramp quickly in a Python-based stack.
  • Strong communication and stakeholder management skills across geographies and seniority levels.
  • Proven ownership mindset: independently taking ambiguous problems, investigating, driving decisions, and delivering production outcomes
  • Prior experience partnering with Front Office / Trading; able to operate effectively with rapid feedback loops and high ownership.
  • Strong communication skills; ability to influence and align with Trading/Functional leads and partner teams in person and remotely.
  • Demonstrated ownership mindset: independently taking ambiguous problems, investigating, driving decisions, and delivering production outcomes.
  • Proven technical leadership (mentoring, design/code reviews, raising team standards).
  • Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.

Preferred qualifications, capabilities, and skills

  • Experience in Commodities Front Office Technology, ideally supporting systematic/quant desks and trader workflows.
  • Experience across deal booking, pricing, and risk systems such as SecDb, Quartz, Athena, RICE (or equivalent platforms).
  • Track record delivering front-to-back workflow integrations across execution, booking, pricing, positions, risk, P&L, and reporting in a multi-team environment.
  • Strong UI/tooling experience (e.g., React/TypeScript and/or similar) and test automation for workflow-critical systems.
  • Experience operating production services with strong observability, incident management, and continuous improvement.

Skills

See also

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