Senior Site Reliability Engineer

Obsidian Security is the leading SaaS security platform, trusted by global enterprises like Snowflake, T-Mobile, and Algolia. We protect 200+ organizations across North America, Europe, the Middle East, Southeast Asia, Australia, and New Zealand, including many of the world’s largest Fortune 1000 and Global 2000 companies. Founded in 2017 and backed by top investors like Greylock, Obsidian was built to close a critical gap: securing SaaS apps where business happens—Microsoft 365, Salesforce, and hundreds more. The company does this by offering a complete SaaS security platform to reduce risk, detect and respond to threats, and prevent breaches at the source. Obsidian was built by leaders who redefined endpoint and identity security at CrowdStrike, Okta, Cylance, and Carbon Black. Now, they’re transforming how SaaS is secured. With AI driving rapid SaaS growth and complexity, agentic AI tools gain privileged access to sensitive data through integrations, creating new risks most security tools miss. Obsidian uniquely detects anomalous OAuth token activity and manages integration risks. Major announcements are on the horizon. Recognizing that SaaS security needs to evolve, Obsidian enables growing organizations to start with a lightweight, prevention-focused browser extension and expand coverage over time. With global momentum, a growing partner ecosystem including SentinelOne, Databricks, and Google Cloud, and a major fundraise ahead, Obsidian is scaling rapidly toward long-term growth and IPO readiness. About the DevOps / SRE Team The DevOps/SRE team at Obsidian ensures that engineering excellence translates into stable, scalable, and high-performing production systems. We work closely with Engineering, Quality Engineering, and Customer Support to deliver end-to-end services that bring code to life and maintain our world-class SaaS security platform. As part of our Sydney team, you will also play a foundational role in building Sherlock — our AI-powered SRE agent — owning the infrastructure that enables autonomous incident detection, root cause analysis, and remediation at scale. What You’ll Do Platform Reliability Support and maintain the service quality of our customer-facing SaaS security platform Address complex challenges around scalability, reliability, observability, and cost efficiency Collaborate with Engineering teams to maintain and enhance Helm charts, application deployment, monitoring, and CI/CD pipelines Embed into the engineering team so that you understand the application deeply Define service verification strategies and implement them as part of the CI/CD process to meet SLAs Improve developer experience by optimizing CI/CD workflows and performance Participate in the on-call rotation, providing 24/7 support in coordination with our global SRE team Monitor, debug, and optimize production infrastructure and services on AWS/GCP Own and evolve the observability stack: design and maintain Prometheus/Mimir metrics pipelines, Grafana dashboards, Loki log aggregation, and distributed tracing (e.g. Tempo, Jaeger, or OpenTelemetry) Define and instrument SLIs/SLOs across services; build alerting strategies that reduce noise and surface actionable signals AI SRE Agent (Sherlock) Own the Kubernetes infrastructure for Sherlock: five independently-scaled worker pools, each tuned for its agent’s compute profile with HPA autoscaling Design and maintain the CloudSQL schema, migration pipeline, task queue (SKIP LOCKED), and pgvector IVFFlat index for 1,000+ RCA entries Build Grafana dashboards covering queue depth, worker latency, agent error rates, accuracy trends, and P50/P95 speed Own and maintain the benchmark CI gate in GitLab that blocks any prompt version merge regressing accuracy >5% or speed >15% Deliver capacity planning and cost dashboards for Sherlock’s GKE node pools By month 3, serve as the primary on-call engineer for all Sherlock infrastructure What We’re Looking For Required 4+ years of experience in a DevOps or SRE role supporting SaaS services on GCP and/or AWS Bachelor’s degree in Computer Science or related field Production Kubernetes experience: authored and owns Deployments, HPAs, and resource limits — not just applied YAML Strong proficiency in Kubernetes, microservices architecture, Helm, GitLab CI/CD, and ArgoCD Deep hands-on experience with the Grafana observability stack: Prometheus/Mimir (metrics), Loki (logs), and distributed tracing (Tempo, Jaeger, or OpenTelemetry) Ability to design SLI/SLO frameworks, build alerting rules, and reduce alert fatigue across complex microservices PostgreSQL fluency: schema design, indexing, migrations, and query optimisation Async / queue-based architecture experience: debugged stuck queues, consumer lag, and duplicate processing Programming proficiency in Python or Go Strong ownership mindset and comfort with production on-call responsibility Highly Desired GCP expertise: Cloud SQL, GKE, IAM, Pub/Sub pgvector or other vector database experience CI/CD pipeline ownership (GitLab CI or GitHub Actions) Familiarity with LLM APIs (Anthropic, Bedrock, or Vertex) Understanding of AI agent design patterns and frameworks Experience with Kafka, Elasticsearch, ScyllaDB, Databricks, Dagster, Sentry, or Kong