Lead Software Engineer, DevOps - Electronic Market Making

As a DevOps Engineer at JPMorgan Chase within the Corporate and Investment Banking Electronic Market Making team, you will help support the reliability, automation, and operational efficiency of a high-performance, latency-sensitive trading platform. You will work with senior engineers to maintain infrastructure, tooling, and deployment pipelines that enable teams across multiple global regions to build, test, and release with confidence. Your work will contribute to the uptime, performance, and scalability of systems operating in live financial markets.

Job Responsibilities

• Support and maintain CI/CD pipeline infrastructure (build orchestration, automated testing, artifact management, and multi-region deployments).

• Implement automation using Python and Bash to streamline operational workflows, environment provisioning, and configuration management.

• Manage and troubleshoot Linux-based (RHEL) production and development environments, including tuning, capacity planning, and resource monitoring.

• Contribute to infrastructure-as-code for consistent environment configuration and deployment topology across development, UAT, and production.

• Build and operate monitoring, alerting, and observability capabilities to support SLA compliance for latency-sensitive trading systems.

• Assist with network configuration and troubleshooting for market data distribution and exchange connectivity in data center environments.

• Follow reliability practices including automated failover, disaster recovery procedures, and post-incident reviews/root-cause analysis.

• Develop and maintain internal developer tooling and self-service platforms to improve engineering productivity and reduce operational toil.

• Collaborate with application engineering, infrastructure, network, and platform teams to drive operational improvements and production readiness.

• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

• Applies 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.

Required Qualifications, Capabilities, and Skills

• Bachelor's Degree in Computer Science or equivalent

• Formal training or certification on software engineering concepts and 5+ years of experience in DevOps, Site Reliability Engineering, or Production Engineering roles

• Proficiency in Python (automation/scripting) and Bash/shell scripting in Linux environments.

• Strong Linux systems administration experience (RHEL/CentOS), including process management, performance diagnostics, and troubleshooting.

• Solid understanding of networking fundamentals (TCP/IP, DNS, load balancing) and practical network troubleshooting.

• Hands-on experience with CI/CD systems (e.g., Jenkins, GitLab CI) and automated test integration.

• Familiarity with configuration management and infrastructure automation (e.g., Ansible, Puppet, Salt) and infrastructure-as-code practices.

• Exposure to containerization and orchestration (Docker, Kubernetes) and supporting distributed, multi-region production systems.

• Ability to support incident management (triage, mitigation, root cause analysis, and remediation) and read/debug C++ codebases sufficiently for operational support.

• 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.

Preferred Qualifications, Capabilities, and Skills

• Experience supporting trading systems or other low-latency environments

• Knowledge of electronic trading concepts: exchange connectivity, market data feeds, order routing

• Familiarity with observability stacks (Prometheus, Grafana, Splunk, ELK)

• Experience with message-oriented middleware or pub/sub systems (AMPS, Kafka)

• Understanding of Equities, Options, and Futures market structure

• Experience working in regulated financial environments