Sr Lead Software Engineer - Java Fullstack/ AI

Lead a global scrum team to deliver on commitments, taking full ownership of business results. You will work closely with Product partners, collaborating and influencing direction. You bring technical solutions to business problems, offering your perspective on how technology can make the product better and deliver results for our clients.

Proactively identify opportunities for improvement and suggest new ideas that drive meaningful impact. You are opinionated about how technology can elevate the product and are always looking for ways to deliver better outcomes for our clients.

Integrate AI into everything you do, both in the solutions you deliver and the way your team works. You bring ideas from a technology perspective on how AI can solve real business problems and accelerate delivery. You encourage and mentor developers to adopt AI-first development approaches, fostering a culture of innovation and continuous improvement.

Set a clear long-term vision for the platform, architecting for scale, resilience, and flexibility. Design and evolve robust, secure, and adaptable solutions that meet future business needs. Champion best practices in system design, integration, and modernization, and set high standards for documentation and design patterns across teams. Exemplify architectural excellence, setting the tone for others and raising the bar for the team. Proactively address technical debt to keep the team focused on delivering value and advancing the platform.
 

Lead by example and model the behaviors we want from every developer. You are a culture changer who takes the team from the status quo to the next level. You enjoy leveling up the team, pushing them to new heights, and supporting junior developers as they grow into senior technologists. You share knowledge, and are passionate about elevating your team’s capabilities.

Develops secure and high-quality production code, and reviews and debugs code written by others

Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.

Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

Drives decisions that influence the product design, application functionality, and technical operations and processes

Serves as a function-wide subject matter expert in one or more areas of focus

Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

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 modern architectures based on microservices, REST and Graph QLs APIs, NoSQL stores, and kafka eventing

Experience building AI native applications using Claude Code.

Knowledge in AWS or similar cloud platforms. Experience working through the entire lifecycle of at least 2 large, complex application build-outs from scratch and delivery for either a large financial organization or a top-class technology product team

Knowledge of CI/CD, DevOps tool chain, software monitoring, and a test-driven approach to agile delivery

Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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; experience coaching senior engineers/leads on compliant usage patterns and controls.

Ability to tackle design and functionality problems independently with little to no oversight
Practical cloud native experience

Preferred qualifications, capabilities, and skills

Skilled at partnering with Product, collaborating, influencing, and constructively challenging to achieve the best outcomes.