Job responsibilities
Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
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
Design, develop, and maintain scalable applications using Java/J2EE and/or Python, hands-on experience with agentic AI frameworks, and deep knowledge of NLP, ML, and cloud-native AI deployment on AWS (including SageMaker and Bedrock).
Experience leading AI-powered products as a Product Owner or Product Manager is required, along with a strong understanding of financial services.
Lead the integration of AI technologies into existing systems, utilizing Natural Language Processing (NLP) and Machine Learning (ML) frameworks to enhance client onboarding processes and improve user experience. Collaborate with data scientists to develop and deploy predictive models.
Implement cloud-based solutions on AWS, leveraging services such as EC2, S3, and Lambda. Champion agile methodologies within the team, facilitating sprint planning, daily stand-ups, and retrospectives to ensure timely delivery of high-quality software
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.
Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines
Experience leading a product as a Product Owner or Product Manager
Ability to present and effectively communicate with Senior Leaders and Executives
Understanding of the business, financial services is required
Preferred qualifications, capabilities, and skills
Developing and refining prompt engineering and multi-turn agent interaction design, expertise in agent observability and evaluation tooling, and domain knowledge in client onboarding processes.
Domain knowledge, client onboarding is preferred
