Lead Software Engineer
Employment Info
JOB SUMMARY
Requirements
- 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 proficiency in one or more programming languages, with strong practical experience in a large corporate environment (e.g., Java / J2EE and related ecosystem); experience with database querying languages.
- Proficient in all aspects of the Software Development Life Cycle and strong understanding of agile methodologies, including CI/CD, application resiliency, and security.
- Demonstrated experience leading effective use of approved AI-assisted software development tools (coding, code review, test acceleration, troubleshooting) and setting team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs/outputs, adherence to resiliency and security expectations); experience coaching engineers on safe, compliant adoption.
- Demonstrated knowledge of software applications and technical processes within at least one technical discipline (e.g., cloud, AI/ML, mobile, etc.).
- Practical cloud-native experience.
- In-depth knowledge of the financial services industry and IT systems.
Responsibilities
- Executes creative software solutions, including design, development, and technical troubleshooting, with the ability to think beyond routine approaches to build solutions and break down complex technical problems.
- Develops secure, high-quality production code and maintains algorithms and services that operate reliably with dependent systems; reviews, debugs, and improves code written by others.
- Produces and maintains architecture and design artifacts for complex applications; ensures design constraints (security, resiliency, performance, scalability) are realized in implementation.
- Drives team adoption of enterprise-authorized AI-assisted engineering practices 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 setting consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns.
- Applies strong knowledge of the SDLC toolchain (CI/CD, automation, quality, observability), including enterprise-authorized AI-assisted development and automation capabilities, to increase the value realized from automation.
- Identifies opportunities to eliminate recurring issues and/or automate remediation to improve the operational stability of software applications and systems.
- Gathers, analyzes, and synthesizes insights from large, diverse datasets, developing visualizations and reporting in service of continuous improvement of applications and systems.
- Proactively identifies hidden problems and patterns (including from data and operational signals) and uses insights to improve coding hygiene and system architecture.
- Contributes to software engineering communities of practice and events that explore new and emerging technologies; mentors engineers and strengthens a culture of diversity, opportunity, inclusion, and respect.
- Leads evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability within existing systems and information architecture.
Desired Qualifications
- Familiarity with modern front-end technologies.
- Exposure to cloud technologies
Are you interested in this position?
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