Manager of AI Engineering

Solovis

$130K — $160K *
US-AnywhereRemote in United States
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Hands-on experience managing agentic AI development teams.
  • Understanding of agentic systems, including scoping, failure modes, and testing needs.
  • 5+ years of software engineering experience, with 2 years in a management role; strong senior engineers are welcome to apply.
  • Experience in PE-backed, lean B2B software companies with revenue between $75M to $300M.
  • Hands-on experience with acquisition integration and ownership of processes.
  • Strong financial acumen, capable of building and defending cost models for projects.
  • Ability to set and uphold high standards in a fast-paced environment.

Responsibilities

  • Design and own KPI framework focusing on velocity and defect rates.
  • Establish AI proficiency standards and manage performance across the organization.
  • Drive the adoption of agentic workflows, focusing beyond just tooling usage.
  • Lead the first AI-augmented initiative in brownfield modernization.
  • Conduct capacity planning, engage existing partners and outline the future budget model.
  • Align stakeholders on roadmap commitments and manage delivery risks proactively.

Benefits

  • Opportunities for professional development in AI and management.
  • Collaborative work environment focused on high accountability and lean processes.
  • Engagement in cutting-edge AI projects and initiatives.
  • Participation in the strategic direction of a growing engineering team.
Full Job Description
Manager of AI Engineering

We are looking for an engineering manager who has led agentic AI teams and knows what AI-native delivery requires in a lean, high-accountability environment. This role owns the delivery engine for a combined engineering org going through integration, modernization, and a full shift to agentic development patterns.

Key Responsibilities

  • KPI framework design and ownership: velocity, escaped defect rates, ramp time, cost per story point, and regression coverage
  • AI proficiency standards: set the 90-day expectation across the org and own performance management for non-progressors
  • Agentic workflow adoption across the team, not just tooling familiarity
  • Brownfield modernization: finalize scope and lead the first AI-augmented initiative using agentic development patterns
  • Capacity planning: assess existing delivery partners, build new channels, and produce the model for next year's budget
  • Stakeholder alignment: support roadmap commitments, surface delivery risks early, and manage expectations across product and business partners


Qualifications
  • Hands-on experience managing agentic AI development teams
  • Working understanding of agentic systems: how they are scoped, how they fail, how they are tested, and what they require from the engineers building them
  • 5 or more years of software engineering experience, including 2 or more years managing individual contributors. Strong senior engineers making a first move into management are encouraged to apply
  • Track record in PE-backed, lean B2B software companies ($75M to $300M revenue)
  • Hands-on acquisition integration experience at pace, with ownership not just involvement
  • Financial acumen. You build your own analyses and can defend story point cost models to engineering leadership and finance stakeholders
  • You set high standards, hold others to them, make decisions with available information, and do not wait for consensus


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