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.
