VP of Engineering

Accountabilities

• Technical Vision & Architecture: Define and drive the technical vision, architecture, and engineering strategy for the core AI-powered product and its supporting systems.
• AI & Computer Vision: Lead the development and evolution of AI/ML pipelines, computer vision systems, and production-grade machine learning capabilities.
• Distributed Systems: Guide the design and scaling of distributed systems, backend services, and full-stack technologies capable of supporting a growing product and customer base.
• Infrastructure & MLOps: Oversee MLOps capabilities, cloud infrastructure, systems architecture, deployment practices, and the reliability and scalability of engineering platforms.
• Engineering Organization: Lead engineering across three primary pillars: Computer Vision and AI, MLOps and Systems Infrastructure, and Platform Engineering.
• People Leadership: Directly manage team leads and senior engineering leaders, providing coaching, feedback, mentorship, and career development.
• Engineering Culture: Build and maintain a high-performing, accountable, collaborative, and technically rigorous engineering culture.
• Best Practices: Establish consistent engineering standards, architectural principles, development practices, and quality expectations across teams and projects.
• Product Partnership: Work closely with Product, Solutions, and executive leadership to define roadmaps, establish priorities, and align engineering investments with business objectives.
• Customer Delivery: Ensure engineering teams consistently deliver high-quality, reliable, and scalable solutions on schedule to meet customer needs.
• Strategic Leadership: Participate in senior-level discussions around company strategy, technology direction, organizational growth, and long-term product development.
• Organizational Scaling: Help scale engineering processes, teams, systems, and technical infrastructure to support continued high-growth expansion.
• Technical Problem-Solving: Provide hands-on technical guidance on complex architecture, AI systems, infrastructure, and software engineering challenges when deeper technical leadership is required.

Requirements

• Engineering Experience: 12+ years of professional software engineering experience, ideally spanning SaaS, infrastructure, and AI systems.
• Leadership Experience: 6+ years leading engineering teams in a hands-on capacity, with demonstrated success managing and developing technical leaders.
• Multi-Team Management: Proven experience managing multi-team engineering organizations and coordinating technical execution across multiple disciplines.
• AI/ML Expertise: Significant experience with AI and machine learning systems is required, preferably with direct experience in computer vision.
• AI SaaS Background: Experience building or scaling AI-driven SaaS platforms in production environments.
• Startup Scaling: Demonstrated experience scaling engineering organizations, products, and technology infrastructure within high-growth startup environments.
• Architecture: Strong understanding of distributed systems, backend architecture, scalable services, and modern full-stack systems.
• MLOps & Infrastructure: Deep familiarity with MLOps pipelines, cloud infrastructure, deployment systems, monitoring, and production machine learning operations.
• Technical Depth: Ability to remain hands-on and provide credible technical leadership while operating effectively at an executive and organizational level.
• Strategic Thinking: Ability to connect technical architecture and engineering priorities with broader product, customer, and company objectives.
• Communication: Excellent communication and collaboration skills, with the ability to work effectively with engineers, product leaders, solutions teams, and executives.
• People Development: Strong coaching, mentoring, delegation, and organizational development capabilities.
• Industrial Experience: Experience working with energy, utilities, or other industrial systems is a plus.
• Geospatial & Imaging: Experience with drones, imagery, geospatial technologies, or related data systems is advantageous.
• Work Authorization: Candidates must already be authorized to work in the United States, as visa sponsorship is not currently available.

Benefits

• High-Impact Leadership: Opportunity to shape the technical direction of an AI-driven platform addressing real-world challenges in the energy and utility sector.
• Technical Scope: Broad ownership across AI, computer vision, MLOps, infrastructure, distributed systems, and platform engineering.
• Executive Influence: Direct partnership with Product, Solutions, and executive leadership on technology strategy and company direction.
• Organizational Impact: Opportunity to build and scale a high-performing engineering organization and develop future technical leaders.
• Innovation: Work at the intersection of artificial intelligence, computer vision, cloud infrastructure, and industrial technology.
• Growth Environment: Join a fast-growing startup where engineering leadership can have significant influence on products, processes, and organizational development.
• Remote Work: Remote position within the United States.
• Professional Development: Opportunity to work alongside experienced engineers, product leaders, and technology professionals on complex AI and software challenges.