Senior AI Security Engineer

Samsara is the pioneer of the Connected Operations Cloud, helping organizations that depend on physical operations use IoT data to improve safety, efficiency, and sustainability. The Senior AI Security Engineer will strengthen and stress-test Samsara’s security posture by applying frontier AI to software, cloud, hardware, and firmware security, while shaping the company’s AI security strategy.

Responsibilities:

• Deliver accurate, consistent security assessments of Samsara's software, code, and firmware, evaluating their resilience against AI-driven/adversarial attacks, and implementing fixes
• Create and translate general AI security findings into Samsara-specific fixes for our application security layer— including adapting techniques built for software to apply to hardware and embedded firmware
• Build and pressure-test novel AI-enabled security tooling and workflows, then drive adoption of what proves valuable across the broader security org
• Partner cross-functionally with engineering, hardware, and leadership (including VP-level threat modeling sessions) as Samsara's go-to expert on AI-related security risk
• Help define & drive Samsara's medium- and long-term strategy for adopting AI safely and effectively within security operations
• Use frontier AI/LLM tools (e.g., Anthropic's and OpenAI's cybersecurity-specific programs) hands-on for both offensive validation (red-teaming our own systems) and defensive tooling — required experience integrating, securing, or red-teaming AI-enabled systems (e.g., LLMs, agentic workflows, prompt injection/adversarial testing) is essential to this role
• Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices

Requirements:

• 8+ years of experience in application security, vulnerability management, threat modeling, offensive security, or a closely related discipline, with demonstrated application fix impact and influence across a large part of an organization
• Hands-on experience applying AI/LLM tools to real security workflows (not just using AI as an end user) — e.g., building with APIs, agents, or automation to support security use cases
• Experience conducting technical security assessments (e.g. offensive security or validation exercises) across both software and hardware/firmware environments
• Experience in creating solutions for secure code with engineers using languages such as GoLang
• Experience developing AI and agentic solutions using Github, and developing within AWS cloud
• Experience with AI-specific attack techniques (prompt injection, jailbreaks, model/agent abuse) for vulnerability management and application security
• Experience building or validating security controls for agentic AI, RAG systems, or LLM-integrated platforms
• A track record of driving org-wide security strategy or presenting technical findings to senior/executive stakeholders
• Relevant industry certifications (e.g., OSCP, GIAC, CISSP) or AWS certifications