Senior Security Engineer, Mysten Labs

• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
• 5+ years in security engineering, detection and response, or infrastructure/SRE with a security focus, including hands-on incident response on endpoints and in the cloud
• Experience operating an EDR, writing and tuning detections. Knowledge of macOS and Linux internals as attackers use them: persistence, credential theft, process injection, living-off-the-land binaries
• Experience building or operating telemetry pipelines and a SIEM or security data lake at TB scale. Strong SQL, including detection logic over large datasets
• Hands-on production engineering: Linux, containers, Kubernetes, at least one major public cloud, infrastructure as code, monitoring and alerting
• Proficiency in Python or Go, and comfort with Rust or willingness to work in it (most of Mysten's stack are Rust)
• Working knowledge of identity: SSO (OIDC/SAML), phishing-resistant MFA, device trust, and how session and token theft work
• Strong written communication: can run an incident channel and write the post-mortem
• Interest in the web3 space is required

Desirable

• Build and operate the Security Observability & Data Platform (tens of TB/month and growing). This covers ingestion, normalization and retention, plus the query and detection layer on top. Detections are code: tested, reviewed, and measured for precision
• Own endpoint security across the fleet: deploy, tune and respond with EDR; run and configure binary authorization; and set hardening baselines with IT Operations
• Lead threat hunting, internal investigations and insider-threat work. Handle security incidents end to end: triage, containment, forensics, root cause, and the control that prevents a repeat
• Build the next generation of security services and run them in production: zero-trust AuthN/AuthZ, a uniform blocking service, an application proxy, asset inventory, developer portal, and compliance as code
• Build and run the agent platform (local and Kubernetes). Use LLM agents to automate triage, enrichment, investigation and response, with deterministic checks wherever a model's answer isn't enough
• Review infrastructure and cloud designs (Kubernetes, AWS/GCP, bare metal, CI runners) for security, and help engineering teams adopt the shared services instead of building their own
• Run red-team and adversary-emulation exercises, and turn the results into detections and fixes
• Write runbooks and post-mortems that someone who wasn't in the room can follow at 3 a.m