Staff/Senior Staff Software Engineer - Full Stack
@ ZooxStaff/Senior Staff Software Engineer - Full Stack
About the job
Zoox develops autonomous vehicles and ecosystems, aiming to redefine urban mobility. This role focuses on leading full-stack development for Geofencer, a critical geospatial platform affecting real-world vehicle operation.
Requirements
- 10+ years industry experience
- Fullstack development proficiency
- Python backend expertise
- React with TypeScript skills
- Linux and cloud infrastructure
Qualifications
- Bachelor's in engineering or related
- Experience with geospatial systems
- Technical leadership skills
- Experience in safety-critical systems
Full job description
The Software Systems Infrastructure team is responsible for aiding the Software Systems organization with all its internal tooling needs, development processes and ensuring that all safety-critical software meets a high safety bar for production vehicles. We are a fullstack, high-paced software engineering team.
In this role, you will be a technical lead for a tool called Geofencer - Zoox's geospatial platform for defining where and how our autonomous vehicles operate. Geofencer is the system of record for geofences, road-network annotations, pickup/dropoff zones, and released Plans of Record that flow directly to the fleet — making it one of the highest-leverage tools at the company: a change made in this application changes where robotaxis drive in the real world. You will own architecture and delivery across the full stack, from an interactive map-editing frontend to geospatial backend services and release pipelines, working closely with mapping, autonomy, operations, and safety teams. As a team lead, you'll take technical ownership for the whole system including delivery of features, set technical direction, drive quality and correctness in a safety-critical domain, and mentor engineers across the team.
In this role, you will:
- Lead the design and development of Geofencer across the stack: a React/TypeScript single-page application with rich interactive map editing (deck.gl, Mapbox), and Python backend services (FastAPI, SQLAlchemy/GeoAlchemy2, Celery) on PostgreSQL/PostGIS.
- Own core geospatial data workflows: versioned geofence editing, road-network annotation, drivable-area computation and connectivity validation, and the Plan of Record release process that publishes operational constraints to the fleet.
- Integrate with the broader Zoox ecosystem: the Zoox Road Network (ZRN) map graph, S3 artifact pipelines, downstream fleet and mission systems, and ML-assisted annotation workflows.
- Operate production infrastructure: Bazel builds, Docker/Kubernetes deployment, observability (Grafana, Sentry, OpenTelemetry), and CI/CD and whip up quick scripts and tools to automate tasks — data migrations, bulk annotation operations, metrics generation.
- Drive cross-functional alignment with operations, mapping, and autonomy stakeholders; translate ambiguous operational needs into scalable technical solutions; and mentor engineers on the team.
Qualifications
- Bachelor's degree in an engineering, mathematics, or related field
- 10+ years of industry experience building and operating production fullstack systems on large code bases
- Strong proficiency in fullstack development: Python backend services (FastAPI/Flask/Django or similar), React with TypeScript/JavaScript (ideally for data-heavy or visualization-intensive UIs), relational databases, async/task-queue architectures, and scripting/automation (Python, shell)
- Experience with Linux, cloud infrastructure (AWS or similar), containerized deployment, build systems, version control, testing methodologies, and CI/CD
- Demonstrated technical leadership: driving multi-quarter projects, setting architectural direction, and mentoring engineers
Bonus Qualifications
Experience with geospatial systems: PostGIS, GDAL/Shapely/Turf, map rendering libraries (deck.gl, Mapbox GL, Leaflet), or road-network/graph data models and building map-based web applications or GIS tooling with safety-critical systems
Robotics, automotive, or aerospace software experience
Familiarity with ML-assisted data pipelines (e.g., VLM-based annotation or labeling workflows)
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