About the role:
We run a distributed, camera-based video monitoring and AI alerting platform. The system spans the full spectrum of modern and legacy infrastructure: an AWS-hosted fleet of Java microservices and workers, a GPU-backed computer-vision inference pipeline, a real-time streaming and presence layer, and thousands of on-premise edge "media boxes" deployed in the field that ingest camera feeds, serve HLS video, and stream events back to the cloud.
This is a reliability-first role. Your primary job is to keep a large, mixed operational estate healthy at scale: meaningful service objectives, trustworthy alerting, sound capacity, tested disaster recovery, and fast, calm incident response. Delivery pipelines matter, but here they exist in service of reliability, not the other way around. We are not hiring a pipeline-and-self-service DevOps engineer who treats operations as a side concern. We are hiring an SRE who owns uptime and operational quality, and who can write the software to make that uptime measurable and automatic.
If you think in SLOs, error budgets, and blameless postmortems, and you are happiest when a noisy, fragile system becomes quiet and predictable on your watch, this is your role.
What you'll keep reliableYou will own the operational health of all of the following:
- Computer-vision / AI models: frame-based inference services running on GPU EC2 (g4dn-class, AWS Deep Learning AMIs), fed by camera frames from S3 and a Kafka (Amazon MSK) event bus, with Redis (ElastiCache) for state. Outputs flow through an alerts pipeline (OutgoingInferenceMessage to SNS/IoT to notification workers).
- Python services: the AI/alerts inference tier and supporting tooling.
- Legacy Java services: ~140 Java 8 services and libraries (REST APIs, SQS/SNS workers, Lambda functions) running on Jetty 9.4, deployed to Elastic Beanstalk, ECS, and Lambda.
- Edge appliances ("media boxes"): Ubuntu 22.04 / Docker Compose appliances managed remotely over AWS IoT Core secure tunnelling, with Cloudflare tunnels for egress. Includes an active CentOS 7 to containerized-stack migration effort.
- Data and messaging backbone: PostgreSQL (RDS) across many schemas, TimescaleDB for analytics, Redis, DynamoDB, Amazon MSK (Kafka), SQS/SNS, and Kinesis.
What you'll do Reliability and operations (the core of the role)
- Own service objectives. Define SLIs and SLOs for the services that matter, manage error budgets, and use them to drive prioritization and change-rate decisions. Make reliability a measured number, not a feeling.
- Make observability trustworthy. Own alert quality end-to-end: high signal-to-noise, alarms that reliably catch the incidents they are meant to catch, and the discipline to turn off a misleading alarm until it is fixed properly. Build the dashboards and the custom metrics, exporters, and instrumentation (CloudWatch, OpenTelemetry) needed to see the system clearly.
Delivery and platform (in support of reliability)
Nice to have
How we work, and what we expect from this hire:
These principles reflect lessons we take seriously. The right candidate already operates this way: