Manager, AI-Native Software Engineering

Role Description

The Manager, AI-Native Software Engineering leads a team of engineers building and maintaining the platforms that power Libra Solutions’ products within an agentic delivery model. This role combines people leadership with technical oversight, and is accountable for delivering high-quality software, growing the team’s AI-native capabilities, and ensuring the team operates effectively in a pod model where AI agents are active participants in the SDLC alongside human engineers.

The ideal candidate is a player-coach who manages and develops a team effectively while staying connected to the technical work. They bring strong engineering depth in the Microsoft / Azure stack, proven people leadership skills, and demonstrated experience leading teams. This role partners closely with Engineering, Product, and business stakeholders to deliver high-quality software at scale.

This position reports to the Director of Engineering and can be based in any of our office locations in Denver, CO, Huntersville, NC, Rosemont, IL or Las Vegas, NV. We welcome strong remote candidates, with occasional travel to Las Vegas as needed.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent professional experience
• 7+ years of professional software development experience
• 2+ years of people management or team leadership experience
• Strong hands-on background in C# / ASP.NET Core, Entity Framework Core, SQL Server / Azure SQL, and React or Angular
• Experience with Azure DevOps, CI/CD pipelines, and cloud-native deployment practices on Azure
• Experience partnering closely with engineering, product, and business stakeholders in an agile delivery environment
• Demonstrated ability to lead, develop, and retain a high-performing engineering team
• Strong problem-solving, communication, organizational, and coaching skills
• Hands-on familiarity with AI-assisted development tooling (GitHub Copilot, Claude, Azure OpenAI) and a demonstrated commitment to building AI-native engineering practices
• Experience leading teams within agentic or AI-accelerated delivery models, or a clear understanding of how agentic workflows change team rhythms, role expectations, and quality ownership

Requirements

• Manage, mentor, and develop a team of software engineers across all experience levels
• Conduct regular 1:1s, provide timely and constructive feedback, and support each engineer’s professional growth and career development
• Partner with recruiting to grow the team by attracting and hiring engineers aligned with the team’s AI-native technical direction
• Set clear expectations, foster accountability, and build a culture of trust, collaboration, and continuous improvement
• Address performance issues constructively and proactively
• Own the team’s delivery commitments; ensure features, bug fixes, and technical investments are completed on time and meet quality standards
• Participate in sprint planning, backlog refinement, and prioritization discussions with Product and stakeholders
• Remove blockers, manage dependencies, and ensure the team has what it needs to execute effectively
• Monitor and continuously improve team velocity, predictability, and delivery health within the agentic pod model
• Maintain strong technical engagement: participate in architecture discussions, code reviews, and technical planning
• Ensure the team adheres to engineering standards for C# / .NET, API design, database patterns, front-end development, and CI/CD using Azure DevOps
• Identify and address technical debt; champion sustainable engineering practices
• Drive adoption and effective use of AI-assisted development tools across the team
• Partner with other engineering leaders to define and uphold organizational AI development standards, prompt engineering practices, and AI output review requirements
• Track and evaluate team-level engineering metrics to identify systemic issues and drive continuous improvement
• Use data to communicate engineering health, technical decisions, tradeoffs, and statuses clearly to stakeholders and leadership
• Contribute to engineering-wide initiatives including hiring practices, standards, tooling, and process improvement

Benefits

• Competitive compensation
• Medical, dental, vision, and life insurance plans
• 401k match
• Paid time off