Senior Manager of Software Engineering - Java Full Stack

• People leadership (direct reports): Hire, onboard, coach, and develop engineers; provide performance feedback; build growth plans; foster an inclusive, high-ownership culture.
• Player/coach technical leadership: Remain hands-on while leading—drive system design, contribute code, perform code reviews, troubleshoot production issues, and mentor through pairing and design sessions.
• Own technical outcomes for a platform/portfolio: Accountable for architecture, engineering quality, delivery predictability, reliability, and operational excellence across a set of finance solutions.
• Backend leadership (Python + Java): Lead design and implementation of RESTful services and microservices using Python and Java, selecting fit-for-purpose patterns and ensuring maintainability and testability.
• Full-stack delivery: Guide frontend development (React and modern JS practices) and ensure clean API contracts, strong UX performance, and secure-by-design implementations.
• Data platform leadership: Drive strong practices in data modeling, schema design, and performance for Oracle and PostgreSQL, and scalable key-value/document access patterns for DynamoDB.
• Modernization & automation: Drive modernization initiatives (legacy automation, upgrades, migrations), reducing manual effort and improving control/traceability of key processes.
• Operational rigor: Improve CI/CD, release discipline, observability (logs/metrics/tracing), incident response readiness, and runbooks; raise the team’s production ownership.
• Stakeholder partnership: Work closely with Finance, Product, Operations, and Technology partners to shape roadmaps, manage tradeoffs, and communicate status and risk clearly.
• Global execution: Lead effectively across distributed teams (US/India), ensuring consistent standards, healthy delivery cadence, and strong collaboration.
• Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise
• Proven experience as a hands-on engineering leader with direct reports (e.g., Lead Engineer / VP-level), combining people leadership with technical ownership and delivery accountability.
• Strong backend engineering experience with both Python and Java, including building and supporting production-grade services.
• Experience building RESTful APIs and applying microservices/distributed systems patterns (e.g., resiliency, idempotency, versioning, backward compatibility).
• Proficient in web application development (HTML, JavaScript) using modern frameworks such as ReactJS (Angular/Node experience welcome).
• Strong experience with databases and data access patterns including:
• Oracle and/or PostgreSQL: advanced SQL, performance tuning, indexing, and query optimization
• DynamoDB: partition/sort key design, access pattern-driven modeling, and performance/scalability considerations
• Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.

Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.

Preferred qualifications, capabilities, and skills

• AWS knowledge and/or certification (Solutions Architect, Developer, DevOps).
• Hands-on AWS experience, including Compute/container platforms (e.g., ECS/EKS, serverless patterns), Data services and migration approaches (e.g., RDS/Aurora PostgreSQL, DynamoDB design at scale), Infrastructure as Code and automation practices, Observability and operational readiness in cloud environments
• Experience leading modernization programs: legacy automation, on‐prem upgrades, data center moves, and cloud migrations.
• Secure-by-design engineering practices: secrets management, least privilege, vulnerability remediation, and production risk management.