Job description

Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth. We are building a new Physical AI product line at Netradyne — a vision-based platform that monitors activity across physical environments and surfaces safety risks in real time. This is founding-team work, and we're hiring generalists who are excited about building something new. A Founding Product Engineer owns problems end-to-end — from an edge device, through the cloud platform, to the surface a safety manager touches — and moves fluidly between them depending on what the product needs that week. You'll naturally lean toward platform/infrastructure or toward product/experience based on your strengths, but you're expected to have working range across both, not a hard boundary between "backend team" and "frontend team." You talk to customers directly, turn what you hear into what gets built, and take it the rest of the way to shipped. Essential Functions: Platform & infrastructure (lean here if that's your strength): Cloud ingestion and storage — real-time event streaming, time-series and event storage, the data model for safety events and metrics. Multi-tenancy, identity, and access control — multiple customers, multiple sites per customer, role-based access control, authentication and SSO. Infrastructure and DevOps — AWS, containerized deployments, CI/CD, and monitoring across the edge and cloud stack. Product & experience (lean here if that's your strength): Operations dashboard — real-time event feed, alert detail with video clips, site map, zone-violation tracking, risk summaries. Compliance analytics — trend reporting, time-based comparisons, exportable reports for safety and operational record-keeping. Operator scoring and coaching workflow — worker/operator safety scoring, coaching queue, session tracking and completion. Shared, regardless of lean: Agent layer / agentic features — the orchestration layer and conversational/agentic surfaces over safety data (alert triage, auto-coaching drafts, summarization), built on managed services or internal modules where they fit. Rapid iteration with real customers — ship fast, instrument usage, work directly in the field, run pilots alongside live deployments. Qualifications: What we're looking for: Systems thinking — you can reason about a problem end-to-end, from device to cloud to the person using it, and make sound calls with incomplete information. Dynamic range — you move between an infra problem, a product/UX problem, and a customer conversation within the same week without needing to be re-anchored each time. You don't default to the one lane you're most comfortable in. Bias to action, full ownership — given an ambiguous problem, you scope it, build it, ship it, and measure it, without waiting to be told the next step. Direct customer experience — you've worked directly with customers or end users to shape what gets built, not just built to a spec handed down. Baseline technical range: Full-stack comfort: a modern backend language (Go, Python, Java) and, depending on lean, either cloud infrastructure (AWS, containers, CI/CD, distributed/event-driven systems) or modern frontend (TypeScript/JavaScript) and data-dense real-time UI (dashboards, event feeds, video, timelines). Experience designing or working within multi-tenant systems with role-based access control. Fluent with AI-assisted development tools (Claude Code, Codex, Cursor) as part of your day-to-day workflow. 7+ years of software engineering experience. We'd rather have someone with less tenure and real range than more tenure in one narrow lane. Nice to have: Agent orchestration or workflow engines (e.g. Temporal); managed identity platforms (WorkOS, Auth0, Clerk). Data pipelines at scale (Spark/PySpark, time-series); high-volume IoT or sensor data. Building or integrating AI agent features (tool use, conversational interfaces, LLM-powered surfaces) — a strong differentiator. Safety, operations, or compliance software experience. Education: Bachelor's degree in Computer Science, Engineering, or a related technical field. San Diego Pay Range $140,000 — $190,000 USD We are committed to an inclusive and diverse team. Netradyne is an equal-opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status. If there is a match between your experiences/skills and the Company's needs, we will contact you directly. Netradyne is an equal-opportunity employer. Applicants only - Recruiting agencies do not contact. Recruitment Fraud Alert! There has been an increase in fraud that targets job seekers. Scammers may present themselves to job seekers as Netradyne employees or recruiters. Please be aware that Netradyne does not request sensitive personal data from applicants via text/instant message or any unsecured method; does not promise any advance payment for work equipment set-up and does not use recruitment or job-sourcing agencies that charge candidates an advance fee of any kind. Official communication about your application will only come from emails ending in ‘@netradyne.com’ or ‘@us-greenhouse-mail.io’. Please review and apply to our available job openings at [application link] For more information on avoiding and reporting scams, please visit the Federal Trade Commission's job scams website .

Requirements

Must-haves

Platform & infrastructure (lean here if that's your strength):
Cloud ingestion and storage — real-time event streaming, time-series and event storage, the data model for safety events and metrics.
Multi-tenancy, identity, and access control — multiple customers, multiple sites per customer, role-based access control, authentication and SSO.
Infrastructure and DevOps — AWS, containerized deployments, CI/CD, and monitoring across the edge and cloud stack.
Product & experience (lean here if that's your strength):
Operations dashboard — real-time event feed, alert detail with video clips, site map, zone-violation tracking, risk summaries.
Compliance analytics — trend reporting, time-based comparisons, exportable reports for safety and operational record-keeping.
Operator scoring and coaching workflow — worker/operator safety scoring, coaching queue, session tracking and completion.
Rapid iteration with real customers — ship fast, instrument usage, work directly in the field, run pilots alongside live deployments.
Systems thinking — you can reason about a problem end-to-end, from device to cloud to the person using it, and make sound calls with incomplete information.
Bias to action, full ownership — given an ambiguous problem, you scope it, build it, ship it, and measure it, without waiting to be told the next step.
Direct customer experience — you've worked directly with customers or end users to shape what gets built, not just built to a spec handed down.
Experience designing or working within multi-tenant systems with role-based access control.
Fluent with AI-assisted development tools (Claude Code, Codex, Cursor) as part of your day-to-day workflow.
7+ years of software engineering experience. We'd rather have someone with less tenure and real range than more tenure in one narrow lane.
Bachelor's degree in Computer Science, Engineering, or a related technical field.
If there is a match between your experiences/skills and the Company's needs, we will contact you directly.
Netradyne is an equal-opportunity employer.
Applicants only - Recruiting agencies do not contact.
Recruitment Fraud Alert!

Nice-to-haves

Agent orchestration or workflow engines (e.g. Temporal); managed identity platforms (WorkOS, Auth0, Clerk).
Data pipelines at scale (Spark/PySpark, time-series); high-volume IoT or sensor data.
Building or integrating AI agent features (tool use, conversational interfaces, LLM-powered surfaces) — a strong differentiator.
Safety, operations, or compliance software experience.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

airestawsci/cdgopythonjavatypescriptjavascriptllm

Platform: greenhouse
Effort: quick

Benefits

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Vision