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Obvio

AI-powered traffic monitoring and automated enforcement

Full Stack Engineer - Traffic Studies

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeSan Carlos, CA, USANo salary listedIn-person

About the Job

Requirements

  • At least 4 years of professional software engineering experience with meaningful full-stack ownership, including backend services and data pipelines as well as internal tools and front ends.
  • Experience building and operating services on a major cloud platform; AWS is preferred, including ECS/EC2, S3, and IAM.
  • Solid database skills, including schema design, indexing, and query performance on growing datasets using Postgres or a similar database.
  • Experience building internal tools or dashboards using a low-code platform such as Retool or a modern web framework.
  • Experience running production systems, including monitoring, alerting, incident response, and post-incident fixes.
  • Experience orchestrating batch or compute-heavy workloads, such as job queues, workers, or GPU/ML servers.
  • Ability to own systems end to end, balance rapid fixes with codebase quality, automate recurring manual processes, and build data traceability and auditability.
  • Ability to communicate clearly, document requirements, work across engineering, annotation, operations, and go-to-market teams, and re-plan as priorities change.

Responsibilities

  • Own the traffic-study backend end to end, including ingestion from multiple sensor types, vision-pipeline orchestration on ML servers and cloud compute, event extraction, annotation hand-off, statistics, and publishing to the city-facing portal.
  • Automate manual steps such as statistics entry, reprocessing, and report assembly so studies run consistently and with minimal engineer involvement.
  • Design systems so requests for new sensors, metrics, report formats, and shorter timelines can be handled through configuration and small extensions rather than rewrites.
  • Design and evolve the data model, including schema design, indexing, and query performance for growing Postgres datasets supporting the pipeline and internal tools.
  • Maintain monitoring and alerting for vision and event-extraction services, detect stuck or failed studies early, and drive fixes to root cause.
  • Implement counting and violation logic from written specifications, version the logic, and make reported figures traceable to raw data and the logic that produced them.
  • Coordinate with the annotation team on intake, view-quality gates, and delivery dates; coordinate with field operations on deployment timing and data hand-off; and provide the go-to-market team with realistic capacity and lead-time answers.
  • Expose APIs and data endpoints used by annotation and operations tools, including presentation and review managers, calibration tools, audit dashboards, and capacity and status views.

Desired Qualifications

  • Experience with pipelines that consume computer-vision or sensor outputs such as detections, tracks, and radar, or with video and imagery at volume.
  • Experience with data-quality, annotation, or audit workflows.
  • Familiarity with IoT or edge devices and operational issues such as timestamps, connectivity, and uploads.
  • Startup or small-team experience involving end-to-end ownership of a system.
  • Experience building and operating services using AWS, including ECS/EC2, S3, and IAM.

About the Company

Obvio

AI-powered traffic monitoring and automated enforcement

Obvio.ai provides AI-powered traffic monitoring and automated enforcement for municipalities, law enforcement, and traffic management authorities. It detects violations in real time (e.g., stop-sign infractions, speeding, tailgating) and delivers dashboards, automates citations, and offers driver-education tools, with solar-powered hardware for rapid deployment and remote operation. The platform stands out by delivering end-to-end, real-time data and automated workflows that reduce risky violations and save officers time, supported by ongoing service contracts. Its goal is to improve road safety and operational efficiency in smart-city and public-safety contexts by making traffic monitoring and enforcement faster, scalable, and maintainable.

Company size
51-200
Company stage
Series A
Total funding
$28.7M
Headquarters
San Carlos, CA
Founded
2023

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