Infrastructure Security Lead
Together AIalmost 2 years ago
Base Salary
$200k - $300k/yr
Responsibilities
- Own infrastructure security for globally distributed systems as the technical leader of the function.
- Build and lead the infrastructure security team, defining standards and attracting engineers.
- Partner with engineering and infrastructure teams to harden global systems.
- Develop internal security tooling to address security challenges at scale.
- Improve security telemetry, detection, and response to potential security events.
- Identify and remediate vulnerabilities across engineering systems, including authenticated vulnerability scanning of distributed systems.
- Secure AI-specific infrastructure including training clusters, GPU fleets, model artifacts, and inference endpoints.
Requirements
- Hands-on security leadership experience with the ability to lead a team while remaining deeply technical.
- Strong systems and cloud-native software engineering experience with deep proficiency in Linux configuration, security, and administration.
- Fluency with infrastructure automation and infrastructure-as-code using Terraform, Ansible, and/or Salt.
- Experience with security telemetry and detection tools or systems such as OSQuery, Falco, and SIEM, plus vulnerability remediation in distributed systems.
- Pragmatic security judgment and the ability to help teams ship safely and efficiently.
- Curiosity about the security implications of AI systems.
- Preferred qualifications include Go or Rust development, AWS or GCP cloud-native service experience, deep Linux and networking fundamentals, OCP familiarity including OpenBMC, Coreboot, or Linuxboot, and a public security-practitioner footprint through talks, open-source work, or writing.
Benefits
- Full-time position with US base salary range of $200k-$300k+ equity and benefits.
- Startup equity, health insurance, and other competitive benefits.
- Equal employment opportunity for all applicants.
About Together AI
Together AI builds an AI-native cloud platform for developers, offering high-performance inference, fine-tuning/model shaping, and large-scale pre-training on on-demand GPU clusters with APIs and managed services. It emphasizes open-source models that teams can run and adapt, and also provides infrastructure for decentralized and scalable workloads. Founded in 2022 and headquartered in San Francisco, it is privately held and reports notable customers including Cursor, ElevenLabs, Salesforce, and Zoom.