Director of Product, AI

About the role

The Elevator Pitch: Evolv Technology is looking for a Director of Product, AI, a senior individual contributor who will work at the center of our AI engineering and research teams to build the industry's best weapons detection and computer vision capabilities. You will get deep into the mechanics of how we collect data, define annotation standards, evaluate models, run field trials, and deploy detection systems into the real world, translating that work into product decisions to keep people safe. You will embed directly with AI engineering as the product lead for our detection capabilities, operating with the technical depth to make and defend decisions about data, models, and evaluation methodology.

Responsibilities

What Winning Looks Like:

• First 30 days: Pressure-test how we collect data, set annotation standards, evaluate models, and run field trials. Come back with a sharp read on the biggest gaps, risks, and decisions, and a plan to move on them.
• Within 90 days: Ship a prioritized data collection strategy across the scenarios and threats that matter most. Lock annotation, dataset quality, and validation standards with AI engineering. Define the release-readiness bar, including accuracy, false positive/negative rates, latency, throughput, and real-world load, then get alignment on it. Turn field-trial results into real product and model decisions. Build the operating cadence and decision framework that keeps detection performance moving.
• Within 6 months: Own detection. You're the accountable product lead driving data priorities, model evaluation, release readiness, trade-offs, in lockstep with AI engineering and research. Shape the roadmap, balancing performance against latency, compute cost, hardware limits, and customer experience. Make sure every external claim about detection performance is accurate and defensible, and push hard with legal and compliance to get there.
• By the end of the first year: Demonstrate measurable improvement in detection performance and release predictability across priority use cases. Show that the operating mechanisms you established are consistently identifying performance gaps, driving timely decisions, and improving deployed models. Influence the longer-term detection roadmap through clear evidence about customer needs, technical trade-offs, and business impact.

What you'll own:

• AI/ML Lifecycle Ownership: Define data collection strategy; own annotation guidelines; partner on training methodology and validation; define and own model evaluation metrics (false positive/negative rates, detection latency, throughput under real-world load) and release readiness standards; design and run field trials with prospects and customers; use real-world trial results for product iteration.
• Product & Technical Strategy: Collaborate with AI researchers and engineers to define product vision and technical roadmaps; evaluate diverse AI models and technical approaches; analyze trade-offs across latency, accuracy, compute cost, and hardware constraints; oversee feature development from experimentation to production; work with design and product teams to integrate AI capabilities into intuitive customer- and operator-facing workflows; partner with legal/compliance on