Define and enforce architectural standards, code quality benchmarks, and design patterns across the CPQ and Customer-Facing Applications squads.
Conduct hands-on code reviews, pair programming, and technical design reviews to elevate team capability.
Lead adoption of AI-assisted development tools (Cursor) across the team, modeling best practices through daily usage. Partner with the AI Enablement Engineer on frameworks, configurations, and context pipelines.
Own the technical roadmap for both squads, balancing feature delivery, technical debt, and platform modernization.
Set goals, monitor progress, and resolve operational issues across squads. Collaborate with IT leadership and business stakeholders to ensure alignment.
Own performance management for all direct reports: conduct reviews, set goals, manage career development, and address performance issues proactively and directly.
Mentor and develop two Team Leads; identify their strengths and growth areas, assign stretch responsibilities, and coach them from Supervisor toward Manager readiness.
Mentor and coach all direct reports through regular feedback, clear expectations, and development planning, maintaining accountability for individual growth.
Requirements
Bachelor’s degree in CS, Software Engineering, IT, or related field. Equivalent professional experience considered.
7+ years of professional software development experience. 2+ years in a technical leadership role managing development teams of 6 or more.
Strong full-stack background: modern web frameworks, API design, and relational database architecture.
Working knowledge of CI/CD pipelines, infrastructure-as-code, and cloud platforms.
Demonstrated hands-on experience with AI-assisted development tools (Cursor, GitHub Copilot, or equivalent) in production.
Proven track record developing team members: mentoring developers, coaching underperformers, and building team capability over time.
Strong communication skills with ability to translate technical concepts for non-technical audiences and deliver direct performance feedback.