• Provides guidance to immediate team of software engineers on daily tasks and activities
• Sets the overall guidance and expectations for team output, practices, and collaboration
• Anticipates dependencies with other teams to deliver products and applications in line with business requirements
• Manages stakeholder relationships and the teams work in accordance with compliance standards, service level agreements, and business requirements
• Creates a culture of diversity, opportunity, inclusion, and respect for the team members and prioritizes diverse representation.
• Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment 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 establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 12+ years applied experience
• Experience leading technology projects.
• Proficient in automation and continuous delivery methods. Proficient in all aspects of the Software Development Life Cycle.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• In-depth knowledge of the financial services industry and their IT systems. Practical cloud native experience. 
• Deep expertise in core Java, Spring Boot, J2EE, messaging systems (MQ), Oracle, Postgres, Dapr, Flink, Kafka and Apache Iceberg.
• Proficient in UNIX, Apache Tomcat, and SQL; knowledge of Java Script framework is must.
• Proven experience in designing distributed applications and implementing Agile methodologies.
• Strong background in database management, web services, and Oracle (DB DDL, DML, stored procedures). Experience with Selenium for test automation. Demonstrated ability to debug complex systems and drive technical discussions independently.
• Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.

Preferred qualifications, capabilities, and skills

• Experience working at code level
• Exposure to full software development lifecycle in large-scale systems, preferably within the financial industry.
• Financial industry experience is highly desirable.
• Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines