Lead Python GenAI Engineer — AI-Driven Platform & SRE

JPMorgan Chase & Co.; Wilmington (DE); On-site; USD 180,000 - 260,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer Python GenAI within the Corporate Sector's Model Delivery and Platform Engineering team.

You will be a core technical contributor in an agile environment, delivering trusted market-leading technology products securely and at scale. The role focuses on automation, AI-assisted engineering, site reliability, and governance across risk controls, data security, and incident management.

Qualifications

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Advanced development experience in Java or Python, with excellent debugging/troubleshooting skills for complex production issues.
• Hands-on experience with AWS/other clouds and container platforms/orchestration (e.g., Docker, Kubernetes, ECS).
• Experience building scalable data processing and Big Data/ETL pipelines (e.g., Hortonworks, AWS-based solutions).
• Working knowledge of core infrastructure (routers, load balancers, compute, storage, networks, cloud products) and ability to troubleshoot common networking technologies/issues.
• Deep proficiency in reliability, scalability, performance, security, enterprise architecture, and toil reduction, with the ability to implement SRE practices in applications/platforms.
• Proficiency in white/black box monitoring, SLO alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc.
• Ability to learn/evaluate new technologies, teach languages to others, and collaborate across levels and stakeholder groups.
• Strong foundations in software applications/processes, with emerging depth in a discipline, and the ability to solve complex data structures/algorithms problems.
• 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.

Responsibilities

• Designs, codes, tests, and delivers automation (including LLMs/agents) to eliminate manual operational work and streamline AO workstreams’ remediations (e.g., control items, security vulnerabilities, upgrades, and FARM findings).
• Governs application risk, controls, and compliance: owns adherence to firm standards, partners with Technology Risk & Controls, manages Technology Lifecycle Management (TLM), and drives closure of issues/findings (e.g., FARM) through effective remediation and evidence management.
• Owns security and data accountability for the application: ensures strong authentication/authorization, vulnerability and certificate hygiene, and proper data registration/classification plus compliant storage, retention, and disposal.
• Coordinates across product and engineering at scale to prioritize and drive execution with a clear sense of urgency for AO workstreams, including influencing/coaching teams and aligning execution across large developer communities.
• Runs resilient, well-operated production services end-to-end: implements monitoring/logging and anomaly detection, maintains secure network configurations/least privilege, and leads/supports incident, problem, and change management and recovery/resiliency readiness.
• Demonstrates and champions site reliability culture and practices and exerts technical influence throughout the team.
• Leads initiatives to improve the reliability and stability of applications and platforms using data-driven analytics to improve service levels.
• Collaborates with team members to identify comprehensive service level indicators and stakeholders to establish reasonable service level objectives and error budgets with customers.
• Documents and shares knowledge within the organization via internal forums and communities of practice.
• 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.

Skills

Java

Python

AWS Cloud

Docker & Kubernetes

Big Data/ETL

SRE practices

Monitoring/Telemetry

AI-assisted development

Security/Compliance

Problem solving

Tools

Docker

Kubernetes

ECS

Grafana

Dynatrace

Prometheus

Datadog

Splunk

AWS

Job description

JPMorgan Chase & Co. is seeking a Lead Software Engineer Python GenAI within the Corporate Sector's Model Delivery and Platform Engineering team.

You will be a core technical contributor in an agile environment, delivering trusted market-leading technology products securely and at scale. The role focuses on automation, AI-assisted engineering, site reliability, and governance across risk controls, data security, and incident management.