Senior Lead Software Engineer - DevOps with Equities Electronic Trading

About the role

As a Lead Software Engineer within the Commercial & Investment Banking - Markets Tech - Trading / Derivatives Execution Tech team at JPMorgan Chase, you will be an integral part of an agile team enhancing, building, and delivering trusted market-leading technology products in a secure, stable, and scalable way. This hands-on, operations-oriented role focuses on the reliability, performance, and operational integrity of electronic and equities trading systems, with a specific emphasis on FIX protocol connectivity. You will partner closely with trading, technology, and development teams to ensure stable order flow, rapid incident response, and disciplined change execution.

The role emphasizes Python automation, Linux troubleshooting, and Grafana-based observability, with exposure to C++ primarily for issue investigation and collaboration.

Responsibilities

• Execute creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Provide daily production support for electronic trading platforms, including FIX sessions/protocols, connectivity health, and order/trade workflow stability.
• Monitor system health and trading-impacting signals using Grafana dashboards and alerting to improve visibility into latency, errors, throughput, and availability.
• Lead incident triage and restoration activities during service degradation, including structured troubleshooting, stakeholder communications, and post-incident follow-up.
• Perform root cause analysis on recurring issues and implement durable remediation, including runbook improvements, alert tuning, and operational automation.
• Develop secure, high-quality production code by using Python scripts and tools for health checks, operational workflows, reporting, and environment validation.
• Operate and support Kafka on AWS (e.g., Amazon MSK or equivalent) with topic/partition design, consumer groups, throughput/latency tuning, security/permissions, and production troubleshooting.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support). Establish consistent validation standards (secure coding, peer review, automated testing) and promote reuse of effective patterns across the team.
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Troubleshoot Linux-based systems using logs, process and resource diagnostics, and network-level checks relevant to connectivity and application behavior.
• Partner with development teams to investigate complex issues in trading components by reading logs, traces, and diagnostic output, and interpreting findings in contexts where components are implemented in C++.

Requirements

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Advanced proficiency in one or more programming languages, frameworks, and tools (e.g., Python, C++, Bash Scripting, Grafana).
• Demonstrated experience in DevOps and/or SRE in a mission-critical, low-latency environment, with accountability for uptime and incident execution.
• Practical understanding of the FIX protocol.
• Strong Linux troubleshooting capability, including log analysis, process/resource diagnostics, and command-line proficiency.
• Ability to collaborate effectively across trading, operations, and engineering teams, including clear incident communications under time pressure.
• Proficiency in automation and continuous delivery methods, with an advanced understanding of agile methodologies such as CI/CD, application resiliency, and security.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations. Experience coaching engineers on safe, compliant adoption within delivery practices.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile).

Preferred Qualifications

• Knowledge of electronic trading or equities trading environments, including familiarity with order lifecycle concepts and trading-impacting incident patterns.
• Exposure to C++ sufficient to assist with investigation (e.g., reading stack traces, understanding logs and component behavior), without being a primary feature developer.
• Familiarity with ATLAS (or similar internal platform/tooling used for production operations/engineering enablement).
• Familiarity with incident management disciplines, including runbooks, post-incident reviews, alert quality management, and operational readiness practices.
• Basic networking knowledge relevant to troubleshooting connectivity and performance (e.g., TCP/IP behavior, port connectivity, latency sensitivity).

Benefits

• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

Additional details about total compensation and benefits will be provided during the hiring process.