Lead Software Engineer PythonAutomation

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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 firms 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 sharingraising 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

• 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