Job responsibilities

• - Provide guidance to software engineers on daily tasks, team output, and best practices.
• - Hire and develop high-performing talent; maintain a healthy intake pipeline.
• - Foster team morale and encourage collaboration with other teams and partner groups.
• - Drive innovation by solving complex problems and promoting knowledge sharing across teams.
• - Own end-to-end delivery of team epics, ensuring quality and timely execution.
• - Manage stakeholder relationships, including Product Managers, Architecture, and Delivery teams.
• - Build a culture of diversity, inclusion, and respect, prioritizing opportunities for growth and advancement.
• - Identify and address bottlenecks to drive efficiency and improve developer experience.
• - Manage dependencies and build strong relationships with upstream and downstream partners.
• Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.

Required qualifications, capabilities, and skills

• Formal training or certification on Software Engineering concepts and 10+ years applied experience
• 3+ years of managing Teams. 8+ years of industry experience
• - Experience leading technology projects and managing technologists.
• - Identify or troubleshooting application code-related issues. Take active role in code reviews to ensure solutions are aligned to pre-defined architectural specifications. Assist with design reviews by recommending ways to incorporate requirements into designs and information or data flows
• - Advanced understanding of agile methodologies, including CI/CD, Jules/Jenkins, application resiliency, and security.
• - Degree in Computer Science, Engineering, Mathematics, or a related field.
• - Proficiency with technologies like Java, Spring Framework, Spring WebFlux, GraphQL, Angular, Typescript, CSS, Karma, Phantoma.js, NodeJS,Maven, Oracle /postgres DB, SQL, Microservices, Public / private cloud, Apache Kafka.
• - Experience with security tools like Black duck, Sonar, Fortify. Infrastructure Architecture Disciplines, Authentication and authorization principles, Kerberos, Content management.
• - Experience with monitoring tools Dynatrace / Splunk, application management tool Servicenow, versioning tool SVN or GIT.
• - Demonstrated ability to grow and assess talent, manage underperformers, and build force multipliers.
• - Strong stakeholder management and communication skills.
• 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

• - Experience working at code level (dedicating at least 30% of time to code commits).
• - Experience with UNIX/Linux, Shell Scripting, Apache Tomcat, Cassandra, data modeling, Mockito
• - Proven ability to drive innovation and present solutions across teams.
• - Experience managing dependencies and collaborating with cross-functional teams.
• - Ability to create stretch goals and opportunities for team members growth and promotion.