Lead Software Engineer - Python/automation

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Corporate Sector

Lead Software Engineer role focused on designing, developing, and troubleshooting complex distributed systems within the storage domain. The role emphasizes building secure, high-quality production software using Python and driving the adoption of AI-assisted engineering practices to improve code quality and delivery speed. It also involves mentoring junior engineers and leading communities of practice.

What you'd actually do

  1. 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
  2. Design and deliver solutions that address complex business and technical challenges across the storage product domain
  3. Builds secure, high-quality production software in Python, applying best practices in testing, code review, observability, and performance tuning
  4. 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
  5. 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

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • AI-assisted engineering practices
  • responsible AI use in engineering workflows