When you mentor and advise multiple technical teams and move financial technologies forward, it’s a big challenge with big impact. You were made for this.
As a Senior Manager of Software Engineering 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
- Build desk workflow applications that traders rely on: Partner closely with Trading and Functional leads (in person and remotely) to identify workflow pain points, design user journeys, define acceptance criteria, and deliver tooling that improves speed, clarity, and control for the desk.
- Own end-to-end delivery for workflow features: Drive features from concept to production across the SDLC—requirements, design, build, automated testing (unit/integration/contract), release, and ongoing support—ensuring high usability and operational robustness.
- Front-to-back integration through Athena and partner systems: Implement workflow orchestration across Athena and partnering platforms (booking, pricing, positions, risk, P&L, reporting). Coordinate dependencies across multiple teams to land clean, aligned releases.
- Hands-on engineering with “go sort it out” ownership: Deliver high-quality software (Python preferred) and rapidly diagnose/resolve issues with minimal guidance—root cause, fix forward, and improvements to prevent recurrence.
- AI-enabled, spec-driven workflow engineering (day-to-day): Use AI to accelerate real delivery by converting desk requirements into executable workflow specs (BDD-style scenarios), UI/API/event/data contracts, integration mappings, and automated tests—keeping documentation living, changes reviewable, and behavior traceable from requirement to release.
- Technical leadership on a global team: Mentor engineers, lead code/design reviews, raise engineering standards, and build strong partnerships across a globally distributed engineering organization.
- 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**.**
- Creates a culture of diversity, opportunity, inclusion, and respect for team members and prioritizes diverse representation
Required qualifications, capabilities, and skills
- Formal training or certification on Software Engineering concepts and 10+ years applied experience
- Strong fundamentals, system design, testing strategy, operability, secure coding, performance
- Experience leading teams of technologists
- Prior experience partnering with Front Office / Trading; able to operate effectively with rapid feedback loops and high ownership.
- Strong software engineering background in a Python-based stack.
- 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.
- Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines
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.