VP of Engineering

About Troveo

Troveo is building the next-generation data platform to train AI video models. We offer the world’s largest library of AI video training data, offering millions of hours of licensed, training-ready content. Our end-to-end data pipeline connects creators, rights holders, and AI research labs, enabling scalable, compliant, and innovative uses of video for AI applications and model development.

Role Summary

Engineering is central to this mission. Our systems span video ingestion, annotation and labeling pipelines, metadata enrichment, and data delivery, all designed to support high-volume, ML-driven use cases. This is a strategic leadership role for someone who has built and scaled complex, data-centric platforms and understands how machine learning teams actually use data in production.

You will define the architectural and organizational blueprint for Troveo’s engineering function, build and mentor senior leaders, and ensure that the platform evolves in a way that supports both near-term execution and long-term scalability. While this is not a day-to-day coding role, the VP of Engineering is expected to remain technically engaged and be able to dive into architecture, review critical designs, and partner closely with teams on the most complex technical decisions.

This role reports directly to the CEO and is a core member of Troveo’s leadership team.

Technical Strategy & Platform Ownership

• 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.

AI, Data, and Machine Learning Enablement

• 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.

Organizational Leadership

• 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.

Execution & Technical Judgment

• 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.

Cross-Functional Leadership

• 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.

Required Qualifications

• 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.

Why Join Troveo?

• Shape the strategy and operating model of a high-growth venture-backed startup at the intersection of media and AI.
• A collaborative environment with a talented, diverse team of subject matter experts.
• Competitive compensation package with equity upside and benefits.