Hybrid VP of Engineering

at Troveo AI

• Job title: VP of Engineering
• Job type: Full Time
• Experience level: Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Cloud, Distributed Systems
• Location requirements: Hybrid, San Francisco, United States

About the role

• VP of Engineering leading strategic technical direction for Troveo’s engineering organization. Focusing on developing scalable data systems to enhance AI capabilities.

Responsibilities

• Define and own Troveo’s engineering and infrastructure strategy, with a strong focus on machine learning enablement, large-scale data pipelines, and annotation workflows.
• Set architectural direction across backend systems, data infrastructure, and platform tooling, ensuring scalability, reliability, and data integrity.
• Guide long-term technical investments while making pragmatic trade-offs to support near-term product and commercial needs.
• Ensure Troveo’s platform is built to serve ML practitioners, with attention to how datasets are ingested, labeled, versioned, and delivered.
• Oversee the systems that support human-in-the-loop labeling, automation, and quality control at scale.
• Partner with product leadership to align data and ML capabilities with customer needs and evolving AI use cases.
• Build, lead, and develop a high-performing engineering organization, including senior engineers and engineering managers.
• Establish clear ownership, accountability, and decision-making structures as the team scales.
• Create a culture that values thoughtful engineering, operational discipline, and continuous improvement.
• Stay close enough to the work to identify risk, unblock teams, and guide complex technical decisions when needed.
• Review and challenge system designs, architectural proposals, and key technical assumptions.
• Ensure engineering execution is predictable, well-prioritized, and aligned with company objectives.
• Work closely with product, legal, and go-to-market teams to ensure engineering efforts support Troveo’s broader strategy.
• Represent engineering perspectives at the executive level and help translate technical trade-offs into business context.
• Support customer, partner, and investor conversations where technical depth and credibility matter.

Requirements

• 10+ years of experience in software engineering, including significant time in senior leadership roles.
• Proven experience leading teams that build and operate data-intensive platforms, ideally supporting ML or analytics workflows.
• Demonstrated ability to scale engineering organizations while maintaining technical quality and velocity.
• Strong understanding of distributed systems, data pipelines, and cloud-based infrastructure.
• Practical familiarity with machine learning workflows, particularly around data preparation, labeling, and iteration.
• Comfortable engaging deeply in architecture and design discussions without micromanaging execution.

Benefits

• Competitive compensation package with equity upside and benefits.