Posted Jun 1, 2026
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! ## What You’ll Do — Infrastructure & DevOps
Build and maintain infrastructure across GCP and AWS, including Compute Engine, GCS, GKE, Cloud SQL, Cloud DNS, VPC, PubSub, ElasticSearch, ScyllaDB, Databricks, Kafka, Sentry, Dagster, Airflow, Vault, Consul, Kong, and more. - Own infrastructure automation with Terraform/Terragrunt, Ansible, and Helm charts. - Drive microservice delivery via Helm charts, GitLab CI/CD pipelines, and ArgoCD. - Partner with Engineering on capacity planning, performance tuning, and production maintenance. - Partner with InfoSec to address production security issues. - Take on-call shifts and contribute to incident response. - Address tough scalability, stability, and observability problems. ##
Knowledge Capture agent: post-approval LLM summarisation, embedding generation, and structured writes to Jira, Notion, and pgvector. - Investigation state machine application layer: status transitions, retry logic, and dead-letter handling. - Accuracy metric (semantic diff) and speed metric — the signals that drive all prompt improvement decisions. - Regression test framework: replay 50+ historical investigations and gate prompt changes. - Phase 4 implementations: Customer Impact agent, Runbook Executor agent, and Zoom transcription ingestion into the Fact-Finding context.
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