Lead Software Engineer - Python/Java, SRE

Assume a critical role in defining the future of a globally recognized firm and have a direct and significant effect in a realm tailored for top achievers in site reliability.

As a Lead Software Engineer at JPMorgan Chase within the AI/ML Data Platforms team, you will be instrumental in building automation and tooling to improve the scalability and resiliency of the AI/ML and Data Platform that runs the firm. You will also engage in root cause analysis, production changes, budgetary considerations, and staffing challenges. Your experience will be vital in managing and mentoring team members to drive strategic change, both within your team and in partnership with colleagues across JPMorgan Chase & Co.'s global network of innovators.

Job Responsibilities:

• Identify and Implement tooling that will expedite issue detection and resolution for multiple technologies such as Databricks, Snowflake, AWS, Kubernetes, etc.
• Develop and support AI/ML solutions for troubleshooting and incident resolution.
• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems.
• Performs platform design, set-up and configuration, providing engineering support to data engineering teams, Data Science/ML, and Application/integration teams.
• Collaborates with engineering and data teams to optimize infrastructure and deployment processes, focusing on automation and operational excellence.
• Mentor and guide team members to foster innovation and strategic change.
• 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

• Formal training or certification on software engineering concepts and 8+ years applied experience
• Proficient in Python, PySpark, and/or Java application program development with use of automated unit testing.
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Must be able to reduce toil by building new tools to automate repeated tasks.
• Strong understanding of SLI/SLO/SLA and Error Budgets
• Hands-on experience in system design, resiliency, testing, operational stability, and disaster recovery
• Understanding of network topologies, load balancing, and content delivery networks.
• Awareness of risk controls and compliance with departmental and company-wide standards.
• 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 in Data pipelines using Spark
• Exposure to AWS & Databricks Platform administration
• Knowledge of containerization (Docker, Kubernetes) and orchestration
• Familiarity with distributed systems and large-scale data processing