Lead Software Engineer - Python/Automation

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As a Lead Software Engineer at JPMorgan Chase within the Corporate Sector - Infrastructure Platforms - Storage team, youare an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Design and deliver solutions that address complex business and technical challenges across the storage product domain
• Builds secure, high-quality production software in Python, applying best practices in testing, code review, observability, and performance tuning
• 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
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies and partner with cross-functional stakeholders (engineering, product, operations, risk/security) to refine requirements, propose architectures, and deliver outcomes aligned to customer needs and business goals
• Debug and troubleshoot complex issues in distributed systems with leading root-cause analysis and drive long-term fixes
• Mentors junior engineers through coaching, pairing, reviews, and knowledge sharing-raising engineering standards across the team.
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Demonstrated strength in system design, application development, testing strategies, and production operations/stability
• Advanced in one or more programming language(s) and framework(s) (e.g., Python, Java, Fast API, Django, Rest API design, Containers, etc.)
• Experience with distributed systems and messaging, such as RabbitMQ (or equivalent)
• Experience with modern data stores such as Cockroach DB (or equivalent distributed SQL/NoSQL systems).
• 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 with experience coaching engineers on safe, compliant and adoption within delivery practices
• Proficient in all aspects of the Software Development Life Cycle from requitements and design through production support and continuous enhancement
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security, including automation (testing, deployment practices, secure coding, least privilege, incident response, SLOs/SLIs)
• Practical cloud-native experience (e.g., containerization, infrastructure-as-code concepts, managed services), including exposure to AWS

Preferred qualifications, capabilities, and skills

• Experience with storage systems, infrastructure technologies, or platform engineering domains
• Exposure to modern and emerging technologies (e.g., event-driven architectures, service mesh, zero trust patterns, AI-assisted engineering)
• Experience modernizing legacy systems and improving reliability at scale