Head of Product Engineering

Key Responsibilities

• Set and socialize a product roadmap that fuses mobile capture, cloud web application, integrations, and deployment of analytics pipelines to align with Agerpoint’s commercial goals
• Own end-to-end architecture decisions balancing build-vs-buy and ensuring scalability, security, and cost efficiency.
• Direct multiple cross-functional squads (mobile, web, API/integrations) through an OKR-driven agile process, hitting delivery commitments on scope, budget, and timeline.
• Recruit, mentor, and retain a diverse, high-performing engineering team; establishing a culture of innovation, code quality, and continuous learning.
• Implement rigorous reliability practices (automated testing, observability, incident response) to maintain ≥ 99.9 % uptime across global deployments.
• Coordinate with Platform Engineering, Machine Learning, and Data Science teams to accelerate AI innovation and time-to-impact.
• Support IP creation, prototyping novel algorithms and workflows, manage R&D spikes, and coordinate patent filings in computer vision, 3D reconstruction, and geospatial analytics.
• Partner closely with Product Marketing, UI/UX Design and Business Development to translate customer insights into shippable features, cohesive UX, and measurable adoption.
• Manage cloud spend, vendor contracts, and strategic technology partnerships (hyperscalers, drone/UAV providers, agronomy data sources) to optimize ROI.
• Ensure compliance with SOC 2, GDPR, regional data-sovereignty requirements, embedding development security operations into every stage of the development lifecycle.
• Manage external partnerships and integrations with 3rd party data and analytics provider

Qualifications

• 12+ years building and scaling SaaS or platform products; 5+ years in a senior engineering leadership role (Head of Engineering, VP, or small-company CTO).
• Fluency across the full stack (TypeScript/React, Node/Python services, PostGIS/Timescale, Kubernetes, CI/CD (GitHub Actions or similar).
• Proven design chops in cloud + edge architectures (mobile + drone capture, data streaming, GPU/TPU inference) - serves as a player-coach
• Hands-on experience shipping AI/ML products: model lifecycle, feature stores, ML ops, vector databases, latency trade-offs
• Track record of partnering with product, marketing, and external tech vendors to hit ARR, adoption, and cost-efficiency targets
• Excellent communicator who can translate between agronomists, sales execs, and data scientists—and still review a PR when needed
• Experience working with international teams and partners