Staff Application Security Engineer

Please Note: This is a remote position available in the state listed on this job. Additionally, employment with BambooHR is contingent on passing both a background and credit check. AI at BambooHR At BambooHR, we believe in leveraging cutting-edge technology to empower people and transform HR. We’re actively integrating AI into our solutions and workflows to enhance efficiency and drive innovation. To that end, we’re looking to our existing team members and future hires to share this forward-thinking mindset: individuals who are curious about AI’s potential, eager to learn and adapt, and ready to explore how intelligent tools can elevate their work along with BambooHR’s impact on setting people free to do great work. Join us in reimagining the future of HR! Essential Job Duties AI is becoming part of how BambooHR's platform works, from features we build to agents that connect through open protocols. We're hiring a Staff Application Security Engineer to help lead application security through that shift and beyond. You'll set the review bar and standards for agentic systems, and you'll architect the agents our security team uses to scale its work. It is a hands-on, organization-level role for someone who does well in ambiguity and gets results through knowledge, influence, and the help of their team. You will: - Lead security reviews and threat models of AI features and agentic systems — including autonomous agents, MCP servers, and third-party integrations — and keep review playbooks and quality criteria current - Set BambooHR's security standards for AI agents, covering identity and delegated authorization, tenant- and user-scoped data access, safe handling of tool output, tool supply chain, and human-approval requirements, and track adoption as threats evolve - Own the design of agents the security team uses for finding validation, triage, review assistance, and remediation — building and shipping them with clear evaluation criteria, bounded permissions, and human approval gates for high-impact actions - Help developers and security champions build and use agents safely through self-serve guidance and tooling, and advocate for the partner-team investment that work requires - Work with engineering and product leadership to embed security requirements into the SDLC, including design-time and release-time gates for AI features, and make agent-assisted code review, finding validation, and fix suggestions a default part of every team's CI/CD pipeline with clear blocking criteria and a fast exception path - Run security programs that span multiple teams and quarters — setting goals, milestones, and success metrics; maintaining a lightweight intake, prioritization, and retrospective cadence; coordinating dependencies across engineering, product, and operations; and reporting progress, risks, and tradeoffs to leadership - Represent AppSec in architecture forums, harmonize security requirements to reduce duplicated effort across teams, act as a point of escalation, and coach leaders on security tradeoffs - Partner with Legal, Privacy, and GRC on AI governance to close gaps between policy intent and technical implementation through guardrails and automation, including for emerging AI regulations - Train and coach software engineers and engineering teams on secure design and threat modeling, with emphasis on authentication, authorization, multi-tenancy, and AI features - Mentor fellow security engineers on technical direction and career growth, and close skill gaps on the security team through onboarding, training, and mentorship - Participate in an on-call rotation as needed to support incident response and resolve escalated security issues What You Need to Get the Job Done - Bachelor's degree in Computer Science, Information Security, or a related field, or equivalent practical experience - 8+ years of experience in security, including 5+ years of hands-on experience in application security - Experience securing multi-tenant SaaS platforms, including tenant isolation - Cloud and infrastructure security experience (e.g., AWS, Azure, GCP) - Hands-on experience building AI agents or agentic workflows, with concrete examples of how you handled permissions, failures, and validation — production systems, internal tools, personal or open-source projects, and substantial prototypes all count - Demonstrated ability to evaluate the security of AI and agentic systems, including prompt injection, tool and context poisoning, excessive agency, delegated authorization, data leakage, and supply-chain risk in models and tools; familiarity with the OWASP Top 10 for LLM Applications, the OWASP Top 10 for Agentic Applications, or comparable frameworks - Ability to design evaluations for agentic workflows covering task success, false positives and negatives, adversarial cases, and regression checks - Proven experience leading threat modeling (e.g., STRIDE, attack trees) and design reviews for complex applications and APIs -...