5 hours ago
Denver, CO, USA or Seattle, WA, USAStaff+
Base Salary
$203k - $275k/yr
Responsibilities
- Design and implement reusable security architecture and infrastructure for AI tools and agents across identity, data, endpoints, SaaS, and networks.
- Create policies, standards, and reference architectures that make approved and secure AI adoption the default path.
- Own security requests end to end by translating ambiguous needs into requirements, designing and implementing solutions, and supporting them in production.
- Define authentication, authorization, scoped credentials, OAuth governance, least privilege, and human-in-the-loop controls for agents, service accounts, and integrations.
- Govern data access and movement through classification, permission-aware retrieval, AI gateways, DLP, MCP and tool allowlisting, and egress controls.
- Assess AI models and vendors for security, data retention, and training-use terms, and analyze attack paths including prompt injection, unsafe tool use, OAuth abuse, and data exfiltration.
- Build audit logging and detections for prompts, tool calls, agent actions, anomalous tool use, and unexpected data movement.
- Contribute to security initiatives spanning identity, endpoints, SaaS, cloud, networks, detection, and incident response.
Requirements
- Significant hands-on security engineering experience and strong security and privacy fundamentals.
- Experience designing, building, or securing AI systems or integrations such as agents, tool use, retrieval over internal data, or MCP, including understanding of prompt injection, data leakage, and excessive agency.
- Deep experience with identity and access architecture, including SSO, federation, conditional access, MFA, privileged access, identity lifecycle, non-human identities, and OAuth consent and scopes.
- Hands-on experience securing endpoints and SaaS, including device management, device posture, SaaS administration, third-party integrations, and audit logging.
- Strong cloud and network security fundamentals, including cloud IAM, segmentation, and egress control.
- Working knowledge of adversary TTPs and attack paths across identity, endpoint, cloud, and SaaS.
- Demonstrated ability to automate secure defaults, use code for repeatable tasks, and version configurations and agent skills in a repository.
- Demonstrated staff-level judgment in architecture, novel problem solving, trade-off analysis, residual-risk communication, and collaboration with technical and non-technical stakeholders.
- Preferred: experience deploying MCP gateways, LLM proxies, or sandboxed agent execution.
- Preferred: background in threat hunting, incident response, detection engineering, offensive security, or purple team work.
- Preferred: familiarity with the OWASP Top 10 for LLM Applications, MITRE ATLAS, or NIST AI RMF.
- Preferred: experience in regulated or high-trust environments, privacy and data protection programs, or enterprise security architecture at a growing company.
Benefits
- Medical, dental, and vision benefits.
- Paid time off and parental leave.
- Equity, company offsites, and continuous education.
- Commuter benefits and a flexible work environment.
Categories
About Compa
Compa is the leading provider of AI-driven compensation intelligence, built for enterprise teams managing high-stakes pay decisions. Our platform combines live market data with intelligent agents that think like your comp team. Compa’s software automates participation from HCM, ATS, and stock systems, replacing manual submissions and outdated surveys with current benchmarks for cash, stock, offer data, and skills-based compensation. With advanced privacy controls and powerful insights, Compa delivers the clarity and confidence comp teams need to win in the market.