Lambda
Security Engineer
San Francisco Office (Fremont St) (Remote)$266k–$395kfulltimemidAdded 1 month ago
About this role
Lambda seeks a Security Engineer to protect AI cloud infrastructure serving researchers and enterprises. You'll develop threat detections, respond to incidents, harden systems, and build security automation across a fast-moving startup environment.
What you'll do
- Build and tune detection rules in SIEM and EDR systems to identify threats targeting customer data and model weights
- Participate in on-call incident response and lead investigations to prevent future attacks
- Remediate vulnerabilities and security findings in production systems
- Review architecture designs and code changes to provide actionable security feedback
- Develop Python or Go automation tools for evidence collection and vulnerability triage
- Partner with engineering teams across product, data center operations, and IT to implement security improvements
What they're looking for
- Security engineering (5+ years)
- Threat detection and SIEM/EDR tools
- Incident response and investigation
- Linux systems administration
- Python or Go programming
- Cloud infrastructure security
- Vulnerability management
- Security architecture review
Benefits
- Access to Lambda's hosted LLMs for security operations work
- 4 days/week in-office (San Francisco/San Jose/Belmont area) with one remote day
- Opportunity to shape security for AI infrastructure protecting billion-dollar training jobs
- Cross-functional partnerships with product and infrastructure teams
- Work on strategic long-term initiatives alongside tactical security improvements
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Lambda
Lambda builds AI cloud infrastructure providing GPU compute and networking capabilities for researchers and enterprises. The company is hiring for data center operations, security, and facility engineering roles to support large-scale AI compute deployments.
View all jobs at LambdaLikely interview questions
- Walk us through a detection you built or tuned in a SIEM or EDR tool. What threat were you trying to catch, and how did you validate it wasn't generating false positives?
- Describe an incident you investigated end-to-end. How did you move from initial triage to root cause, and what automation or playbook did you build afterward to prevent it?