The AI Site Reliability Engineer will maintain the SaaS security platform's reliability, optimize CI/CD processes, and manage observability stacks, while overseeing the AI-powered SRE agent, Sherlock, and ensuring production stability.
Founded in 2017, Obsidian Security was created to close a critical gap: securing the SaaS applications where modern business happens—platforms like Microsoft 365, Salesforce, and hundreds more.
Backed by top investors including Greylock, Norwest Venture Partners, and IVP, we’ve built a complete SaaS security platform to reduce risk, detect and respond to threats, and prevent breaches at the source. Our team includes leaders who helped define the categories of endpoint and identity security at CrowdStrike, Okta, Cylance, and Carbon Black.
Now, we’re transforming how SaaS is secured—in the era of agentic AI.
Today, Obsidian is trusted by global enterprises like Snowflake, T-Mobile, and Pure Storage. We protect more than 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.
With strong global momentum, a growing partner ecosystem including SentinelOne, Databricks, and Google Cloud, and a major fundraise on the horizon, we’re scaling quickly toward long-term growth and IPO readiness. Join us as we define the future of SaaS security!
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 DoPlatform 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
- 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
- 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
- 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
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