Engineering Manager, Maps
- Market p25–p75
- $239k–$300k
- Verkada p25–p75
- $250k–$269kn=15
- H-1B median · Engineering management
- $240k
- Opened · 30d
- +26
- Closed · 30d
- −17
- Opened · 7d
- +1548% of open
- All engineering management
- 2,294open
Who We Are
Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management.
We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation, more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it.
You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries.
Atlas is the founding engineering team responsible for the Maps mandate at Verkada. Our mission is to transform the physical world into a high-performance, interactive digital twin. We build Verkada Maps, the core rendering engine, tiling infrastructure, and collaborative APIs; that power the visual interface for our entire product ecosystem. Maps launches its private beta today.
The Platform Mandate
We work in a collaborative environment, integrating with key Verkada products including Cameras, Access Control, Sensors, and Alarms. You are responsible for ensuring that as we scale to 8+ product lines, the map remains a performant, unified, and multi editor experience.
What You Do
- Zero-to-One Execution: Act as a "Player-Coach" to build the V1 of our Spatial System from the ground up. You own the initial delivery of our image pipeline and set the technical standards for our collaborative editing protocols.
- Platform Architecture: Lead the design of a modular, plugin-based architecture. You define the SDKs and APIs that allow 8+ Product Teams (Cameras, Access Control, Alarms, etc.) to overlay their specialized data onto our maps seamlessly.
- Data Ingestion Strategy: Oversee the development of the systems that transform unstructured source data—blueprints, CAD files, and high-res imagery—into clean, topologically sound vector data using ML and automated processing.
- Hire & Mentor: Build the founding Atlas team from scratch (4-6 engineers). You establish the engineering culture, from code review standards to architectural RFC processes, focusing on high-performance graphics and spatial math.
- Stakeholder Partnership: Act as the primary technical diplomat for the Maps mandate. You negotiate technical boundaries with other Product EMs to ensure a unified user experience across the entire Verkada suite.
What You Bring
- Execution Bias & Technical Grit: You thrive in the high-ambiguity phase of a zero-to-one build. You are a builder who prioritizes shipping high-utility foundations over perfect abstractions, with a proven ability to translate a high-level vision into a tangible, functioning platform in weeks, not months.
- Strategic Communication: The ability to negotiate technical boundaries with other product teams, ensuring a consistent user experience across the entire Verkada "Command" suite.
- UI Depth & Sophistication: You have led the development of highly complex, state-heavy web or mobile applications. You understand the performance trade-offs of rendering thousands of interactive entities and have a deep grasp of modern frontend architectures (React, WebGL/WebGPU, Swift/Kotlin).
- Data Pipeline & ML Maturity: You have experience building sophisticated data pipelines that handle unstructured data at scale. Whether it's through ML, ETL, or complex geometric algorithms, you know how to turn raw inputs into structured, queryable information.