Lead Software Engineer, AI/ML

What you'll do

• Develop secure, high-quality production code while reviewing and debugging code written by other team members.
• Design and deliver scalable machine learning systems including data pipelines, model training, deployment, and performance monitoring.
• Drive the adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
• Identify opportunities to automate the remediation of recurring issues to improve operational stability for software and ML systems.
• Lead evaluation sessions with external vendors and internal teams to assess architectural designs and technical feasibility.
• Lead communities of practice to promote advanced technologies like MLOps, LLM patterns, and feature stores.
• Establish consistent validation standards for secure coding, peer reviews, and automated testing across the team.

What we're looking for

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Advanced proficiency in one or more programming languages.
• Demonstrated experience leading the use of approved AI-assisted software development tools while ensuring output correctness and security.
• Strong understanding of responsible AI usage, including data sensitivity, secure handling, and coaching engineers on compliant adoption.
• Proficiency in all aspects of the Software Development Life Cycle (SDLC).
• Advanced understanding of agile methodologies, CI/CD, application resiliency, and security.
• In-depth knowledge of financial services IT systems and practical cloud native experience.
• Experience applying ML to servicing or customer operations use cases (preferred).
• Strong MLOps experience including model registries, feature stores, and performance monitoring (preferred).
• Experience with Responsible AI practices in regulated environments and LLM-enabled architectures (preferred).
• Experience building event-driven/streaming architectures and mentoring others on engineering quality (preferred).