About
Leadership built on deep technical craft
I help organizations shape AI strategy and move from experiments to systems that change how work actually gets done—teams, platforms, and operating models included.
I’m Rahman Yousefzadeh, Data Science Manager at Snapp. I work at the intersection of AI strategy and delivery: deciding where agentic systems create leverage, then building the architecture, teams, and operating conditions that make that value stick.
My path started in computer vision research—multi-camera tracking, deep video models, and production AI services—and expanded into engineering leadership as VP of Engineering at Sensifai. Since then I’ve led data science and scale-up work across payments, platforms, and consumer-scale operations.
Today I care less about isolated models and more about strategy that lands in the organization: clear choices, reliable delivery, and agents that earn trust in real workflows.
What I care about
Themes that show up in how I hire, design, and lead.
- Strategy before spectacle Good AI strategy is selective—it names the few workflows worth transforming, and resists building agents where simpler approaches win.
- Ecosystem over demos Agentic transformation fails when tools ship without process, data, and people ready to absorb them.
- Teams that can ship Coaching engineers and scientists, aligning growth with company trajectory, and keeping feedback close to the work.
- Production reality Hybrid architectures, edge and cloud, fraud and safety constraints, latency, and cost—systems that hold under load.
- Public conversation Sharing practical challenges and opportunities of AI agents—including through conversations like the Prompt podcast.
Education
Dissertation on multi-camera people tracking with disjoint views. Distinguished student researcher award, 2009. GPA 18.54/20.
Foundation in software systems, with early work at the intersection of vision and intelligent systems.