Software Engineering Manager – AI Product Development

About Command|Link

Command|Link is a global SaaS Platform providing network, voice services, and IT security solutions, helping corporations consolidate their core infrastructure into a single vendor and layering on a proprietary single pane of glass platform. Command|Link has revolutionized the IT industry by tackling the problems our competitors create. In recognition for our unprecedented innovation and dedication, Command|Link was recognized as the SD-WAN Product of the Year, ITSM Visionary Spotlight, UCaaS Product of the Year, NaaS Product of the Year, Supplier of the Year, and the AT&T Strategic Growth Partner. Command|Link has built the only IT platform for scale that solves ISP vendor sprawl and IT headaches. We make it easy for our customers to get more done, maximize uptime and improve the bottom line.

Learn more about us here!

This is a remote position open to candidates residing in the following states: Alabama, Arizona, Arkansas, Florida, Georgia, Indiana, Kansas, Kentucky, Louisiana, Maryland, Michigan, Mississippi, Missouri, Nevada, New Hampshire, North Carolina, Ohio, Oklahoma, South Carolina, Tennessee, Texas, Utah, Virginia, Wisconsin

About your new role:

We’re hiring a Software Engineering Manager to lead a growing engineering team building and scaling AI-powered products in a capital-efficient, high-growth environment. This role is accountable for delivering product capabilities that drive ARR growth, customer expansion, and adoption, while maintaining strong discipline around cost, margins, and return on engineering investment.

You’ll own execution for a critical product area with direct revenue impact, partnering closely with Product, Finance, and GTM to ensure features are not only shipped quickly, but are economically sound, scalable, and timely. You will focus on getting the right capabilities to market, learning fast from real usage, and continuously adjusting to ensure product features are monetizable. Success in this role is measured by increasing revenue per customer while controlling engineering and infrastructure spend.

This role is ideal for an engineering manager who understands that speed and efficiency are not opposites. You’ll scale teams and systems responsibly, make thoughtful tradeoffs around build vs. buy and AI infrastructure choices, and ensure the organization can grow rapidly without burning unnecessary capital.

Key Responsibilities:

• Own delivery and business outcomes for AI-powered product initiatives, with accountability for ARR impact, adoption, and capital efficiency.
• Lead and grow an engineering team with a focus on output, leverage, and sustainable pace, not headcount growth for its own sake.
• Partner closely with Product, Finance, and GTM to prioritize work based on revenue potential, customer value, and cost-to-serve.
• Drive features that unlock new revenue, expansion, and retention, while improving unit economics.
• Guide architectural decisions with a strong bias toward cost-aware scalability, especially for AI workloads (inference, training, data pipelines).
• Establish engineering practices that maximize engineering ROI, shorter cycle times, fewer handoffs, and predictable delivery.
• Make disciplined tradeoffs to hit market windows while avoiding long-term cost or maintenance drag.
• Track and improve key metrics such as cost per feature, infrastructure spend vs. usage, and revenue per engineering dollar.
• Stay technically engaged through design reviews and selective hands-on work, especially where cost, risk, or scale are involved.
• Build a culture of ownership, accountability, and financial awareness across the team.
• Takes on additional responsibilities and projects as needed to support the success of the team and organization.

What you'll need for success:

• 7+ years of software engineering experience, with 3 to 5+ years in engineering management roles.
• Experience leading teams in capital-conscious, high-growth environments.
• Proven ownership of customer-facing products tied to revenue and margin outcomes.
• Hands-on experience building and operating AI-enabled systems with real cost constraints.
• Strong product and financial intuition, you can reason about tradeoffs between growth, cost, and