Job Summary
The Engineering Manager - Full Stack Engineering will provide people leadership, hands-on technical expertise, and delivery leadership for mission-critical enterprise platforms. This player-coach role will spend approximately 50% of the time contributing to hands-on development while managing one or more Agile/Scrum pods. The position requires strong full-stack engineering expertise, AWS cloud experience, and practical use of AI-assisted development tools to improve engineering productivity, quality, and delivery speed.

Key Responsibilities
• Manage, mentor, and coach full-stack engineers to support performance, career growth, and engineering excellence.
• Lead one or more Scrum pods and support predictable delivery, quality execution, and effective team collaboration.
• Foster a culture of ownership, accountability, learning, experimentation, and continuous improvement.
• Coach engineers on technical practices and effective and responsible use of AI-assisted development tools.
• Actively contribute production code across backend services, frontend applications, and shared platforms.
• Apply high-quality coding, testing, and software design practices.
• Own and review solution designs with a focus on security, scalability, reliability, and observability.
• Conduct code reviews and establish technical and engineering standards.
• Troubleshoot complex technical issues, lead Root Cause Analysis (RCA), and implement long-term improvements.
• Use AI-assisted tools for coding, refactoring, code reviews, quality analysis, architecture ideation, documentation, and optimization.
• Drive adoption of AI-assisted development practices to improve engineering productivity, quality, and delivery speed.
• Evaluate emerging AI capabilities and apply them to appropriate engineering use cases.
• Establish best practices and guardrails for responsible AI-assisted software development.
• Drive sprint planning, backlog grooming, estimation, and delivery tracking.
• Identify delivery risks, technical debt, and capacity constraints and lead mitigation activities.
• Ensure development artifacts align with applicable security, compliance, and regulatory standards.
• Embed reliability, availability, operational excellence, and observability into engineering practices.
• Lead post-release reviews, incident follow-ups, and continuous improvement activities.
• Develop data-driven reports for senior leadership covering delivery status, risks, dependencies, and outcomes.
• Translate complex technical topics into executive-level updates, dashboards, and summaries.
• Collaborate effectively with product, architecture, operations, and business stakeholders.
• Support collaboration across distributed teams and time zones.

Required Qualifications
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 12+ years of software engineering experience with people management responsibilities.
• Demonstrated experience managing Agile/Scrum pods in delivery-focused environments.
• Strong hands-on full-stack engineering experience with modern enterprise systems.
• Strong hands-on experience with Java.
• Strong experience with React.
• Experience with AWS API Gateway.
• Experience with AWS Step Functions.
• Experience designing and developing enterprise applications and services.
• Experience providing technical leadership, mentoring engineers, and supporting engineering teams.
• Practical experience using AI-powered development tools within the software development lifecycle.

Preferred Qualifications
• Proven experience building and leading high-performing engineering teams.
• Experience with Java and Spring Boot for backend development.
• Experience with Node.js.
• Experience with React and TypeScript; Angular or Vue experience is also beneficial.
• Experience designing and developing microservices and REST APIs.
• Cloud-native development experience with AWS services such as EC2, EKS, RDS, and Lambda.
• Experience with CI/CD pipelines and DevOps tools such as GitHub, GitLab, Jenkins, or CloudBees.
• Strong understanding of scalability, performance, resiliency, and security patterns.
• Experience using metrics, dashboards, and reports to monitor delivery health and operational performance.
• Experience applying AI-assisted development tools to improve engineering efficiency and outcomes.