Staff Software Engineer, Product Security (AI)

Location: On-site at the San Francisco or New York office

Annual salary: $200,000–$275,000 USD, plus benefits, equity if applicable, and bonus if applicable

Company

Builds an AI-enabled operational-intelligence platform that helps public safety organizations, government agencies, and private-sector institutions process siloed data and make faster decisions.

What you will do

• Own the product-security roadmap and prioritize initiatives based on risk, customer impact, business needs, and engineering maturity.
• Define security architecture across the platform, focusing on agent sandboxing, software supply chain security, secret management, and cloud security.
• Partner with Product Engineering, Infrastructure, Platform, and other teams to embed secure-design principles throughout the development lifecycle.
• Write and review security-critical production code across key parts of the product.
• Build secure-by-default libraries, frameworks, and tools for engineering teams.
• Identify emerging vulnerabilities and develop pragmatic mitigation strategies aligned with product objectives.

Requirements

• 8+ years of experience in product security, application security, platform security, security-focused software engineering, or related work.
• Experience designing secure architectures and establishing security standards across an engineering organization.
• Strong software-development background with high-quality production Python experience.
• Professional experience identifying and remediating meaningful software vulnerabilities through security engineering, research, penetration testing, bug bounties, CVEs, or comparable work.
• Excellent communication skills and the ability to explain technical security risks through clear product and business tradeoffs.
• Ability to work on-site at the San Francisco or New York office.

Nice to have

• Experience building or scaling product-security programs at a rapidly growing company.
• Experience with AWS and cloud-native security patterns.
• Experience with AI/ML systems and security considerations for LLM-based applications.

Culture & Benefits

• Work closely with deployment teams and users to understand real-world use cases.
• Collaborate across engineering, infrastructure, platform, and product teams.
• Operate in an environment emphasizing empathy, humility, perseverance, and creativity.
• Benefits, potential equity, and potential bonus are included in the compensation package.