Lead Software Engineer - Java/Python, Microservices

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.
• Develops secure high-quality production code, and reviews and debugs code written by others.
• 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.
• Led 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.
• 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.
  • Advanced in one or more programming language(s) - Demonstrated hands on experience with Java or Python and Microservices.
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting).
  • 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.
  • Proficiency in automation and continuous delivery methods.
  • Proficient in all aspects of the Software Development Life Cycle. Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
  • In-depth knowledge of the financial services industry and their IT systems.

  Preferred Qualifications, Capabilities, And Skills

  • Exposure to cloud technologies.
  • Exposure to Financial Models.