About us & the product

We build Camera as a Service (CaaS) — the full glass-to-glass pipeline: cameras deployed at venues worldwide, video ingested to the cloud, automated AI-driven production, and delivery of live streams and highlights to viewers.

Three problem spaces define the work:

• Live streaming at scale — ingest from devices on real, often unreliable venue networks; cloud-side processing and production; low-latency delivery. Game day is the deadline, and it doesn’t move.
• IoT fleet management — provisioning, identity and pairing, remote configuration, health monitoring, firmware updates, and automated self-testing across thousands of cameras, plus operational tooling for support teams.
• Cloud-native production — moving intelligence and state off on-site hardware into distributed cloud services; the services you build are the product.

The role

You’ll own features end to end on the platform that runs sports cameras as a service: distributed backend services for live video at scale and management of a large fleet of connected field devices. You work as a scrum-of-one inside a strong team — you shape the problem with Product, build the backend and UI, cover it with tests, ship it, and own it in production — alongside the people who build the cameras, the algorithms, and the infrastructure underneath you.

What you’ll do

• Design and build distributed services for live streaming at scale: ingest, processing, and low-latency delivery.
• Build IoT fleet management: provisioning, health monitoring, remote configuration, and OTA updates across thousands of cameras.
• Take features from discovery to production: requirements, design, implementation, rollout, and iteration.
• Build operational frontends for fleet and stream management (capable level; not your main focus).
• Own quality: unit, integration, and end-to-end tests, plus contract tests between services.
• Own your services after deploy: observability, alerting, incident response, performance and cost tuning.
• Raise the team’s bar through design reviews, shared tooling, and agent-driven workflows.

What we’re looking for

Required

• 5+ years building production backend systems, with deep experience in distributed architecture (event-driven design, queues and streams, idempotency, failure handling, horizontal scaling).
• Solid cloud and infrastructure skills (AWS, containers, CI/CD, IaC) and strong production observability habits.
• Familiarity with a modern frontend stack (React / TypeScript) to ship complete features without constant handoffs.
• A testing mindset: you treat coverage and release safety as part of the feature.
• Strong product sense and clear communication — turning ambiguous problems into scoped, shipped solutions.
• A team player who gives and takes direct design feedback, shares knowledge, and participates in on-call rotation.
• A proven agentic development track record: structured workflows with tools like Claude Code, and good judgment on when to trust agents vs. verify.

Nice to have

• Hands-on experience with streaming or media pipelines (RTMP / SRT / WebRTC / HLS) and/or IoT device fleets (MQTT, device shadows, telemetry at scale).
• Experience with video/ML pipelines or edge devices.
• Prior ownership of on-call services with defined SLOs.
• Experience with cellular or unreliable-network streaming.
• A passion for sports.

How we work

• Engineers own features and services end to end; the team owns reliability — design reviews, shared on-call, blameless incident reviews.
• On-call is cross-functional, so you learn the whole stack and always have backup.
• Daily collaboration with Product, QA, the algorithm team, DevOps, and support; consumers of your services are a message away.
• Agentic development is our default: shared prompts, workflows, and review practices; we learn from each other’s failures with agents.