Lead Software Engineer Python GenAI

JPMorgan Chase & Co. • Wilmington, DE

1d

About The Position

As a Lead Software Engineer, Python GenAI, at JPMorgan Chase within the Corporate Sector's Model Delivery and Platform Engineering team, you will contribute to an agile team building and delivering secure, stable, and scalable technology products. You will develop critical technology solutions across technical areas and business functions in support of firm objectives. The role combines software engineering, automation and AI-assisted development with application risk and controls, security and data accountability, production service operations, and site reliability engineering. You will influence and coach teams, coordinate execution across engineering communities, improve service reliability using data, and promote responsible, enterprise-authorized AI use in engineering workflows.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience.
• Advanced development experience in Java or Python, with strong debugging and troubleshooting skills for complex production issues.
• Hands-on experience with AWS or other cloud platforms and container platforms or orchestration, such as Docker, Kubernetes, or ECS.
• Experience building scalable data processing and Big Data or ETL pipelines, such as Hortonworks or AWS-based solutions.
• Working knowledge of infrastructure including routers, load balancers, compute, storage, networks, and cloud products, with the ability to troubleshoot common networking technologies and issues.
• Deep proficiency in reliability, scalability, performance, security, enterprise architecture, and toil reduction, with the ability to implement SRE practices in applications and platforms.
• Proficiency in white-box and black-box monitoring, SLO alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, or Splunk.
• Ability to learn and evaluate new technologies, teach languages to others, and collaborate across levels and stakeholder groups.
• Strong foundations in software applications and processes, emerging depth in a discipline, and ability to solve complex data structure and algorithm problems.
• Demonstrated experience leading effective use of approved AI-assisted software development tools for activities such as coding, code review, test acceleration, and troubleshooting, and setting team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure input and output handling, and resiliency and security expectations; experience coaching engineers on safe, compliant adoption.

Nice To Haves

• Current AWS credential, such as Cloud Practitioner, Solutions Architect, SysOps Administrator, or Developer, demonstrating working knowledge of core AWS services, cloud architecture patterns, IAM, VPC networking, monitoring and logging, and cost-awareness practices.
• Recognized automation or DevOps credential, such as in Kubernetes or containers, CI/CD, Infrastructure as Code, or site reliability.

Responsibilities

• Design, code, test, and deliver automation, including LLMs and agents, to reduce manual operational work and streamline AO workstream remediation, such as control items, security vulnerabilities, upgrades, and FARM findings.
• Govern application risk, controls, and compliance by maintaining adherence to firm standards, partnering with Technology Risk & Controls, managing Technology Lifecycle Management (TLM), and driving issue and finding remediation with effective evidence management.
• Own application security and data accountability, including authentication and authorization, vulnerability and certificate hygiene, data registration and classification, and compliant storage, retention, and disposal.
• Coordinate product and engineering teams to prioritize and execute AO workstreams, influence and coach teams, and align work across large developer communities.
• Operate production services end to end by implementing monitoring, logging, and anomaly detection; maintaining secure network configurations and least privilege; and leading or supporting incident, problem, change management, and recovery and resiliency readiness.
• Champion site reliability culture and practices and exert technical influence across the team.
• Lead data-driven initiatives to improve application and platform reliability, stability, and service levels.
• Work with team members to identify service level indicators and with stakeholders to establish service level objectives and error budgets.
• Document and share knowledge through internal forums and communities of practice.
• Drive adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes; establish validation standards including secure coding, peer review, and automated testing; and promote reuse of effective patterns.
• Use Software Development Life Cycle toolchain capabilities, including authorized AI-assisted development and automation tools, to improve the value realized from automation.

Benefits

• Competitive total rewards package with base salary based on role, experience, skill set, and location.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed