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Solovis

Manager of AI Engineering

Posted 6 Days Ago
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
Lead and deliver agentic AI initiatives across engineering, defining KPI frameworks, driving agentic workflow adoption, modernizing brownfield systems, planning capacity and budget, aligning stakeholders, and managing performance for AI proficiency.
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Manager of AI Engineering

Solovis is a leading portfolio management and analytics platform helping institutional investors navigate today’s complex global markets with clarity and confidence. Backed by Insight Partners, were building the next chapter of growth by investing in people and product to raise the bar on quality and client outcomes. Our team is driven by a culture of disciplined execution, humility, and curiosity where AI is at the core of how we operate, innovate, and serve clients. At Solovis, you'll join a tech-forward, growth-minded team that believes in learning fast, thinking big, and delivering meaningful impact for asset owners worldwide.

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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