What You’ll Do

• Develop deep expertise in how enterprise AI platforms—including ChatGPT Enterprise, Microsoft Copilot, Gemini, Claude, Glean, and agentic frameworks—authenticate, access data, request permissions, and interact with corporate SaaS applications.
• Research emerging AI security threats, including prompt injection, tool and agent misuse, RAG poisoning, insecure plugins, excessive agency, data leakage, over-permissioned integrations, and compromised non-human identities.
• Develop threat models for AI applications, agents, models, integrations, identities, permissions, tools, and data flows.
• Design data models that represent AI assets, identities, access relationships, permissions, activities, risks, and attack paths.
• Prototype and deliver production-grade AI security products and capabilities.
• Build backend services and APIs for AI asset discovery, security analysis, risk assessment, detection, investigation, and remediation.
• Build scalable pipelines that ingest, normalize, enrich, correlate, and analyze high-volume security telemetry.
• Write queries and analysis logic that transform raw activity and configuration data into actionable security findings.
• Develop detection rules and behavioral models for suspicious AI and agentic activity.
• Evaluate APIs, audit logs, authentication mechanisms, OAuth permissions, and security controls provided by AI platforms.
• Work with Product Management and customers to understand emerging use cases and turn ambiguous security problems into practical product capabilities.
• Partner with Detection Engineering and Security Research to validate threat hypotheses and improve detection coverage.
• Collaborate with platform and SRE teams to ensure services are secure, observable, highly available, and operationally efficient.
• Improve engineering productivity, pipeline performance, development velocity, and cloud cost efficiency.
• Contribute to technical designs, code reviews, testing strategies, operational readiness, and engineering standards.
• Share research and technical knowledge with engineering teams and help shape Obsidian’s long-term AI security strategy.

What We’re Looking For

• Strong software engineering experience building production-quality backend services, cloud-native applications, data platforms, or security products.
• Hands-on programming experience in one or more languages such as Python, Go, Java, Kotlin, or a comparable backend language.
• Experience designing and building scalable APIs, distributed systems, or data-processing pipelines.
• Strong data analysis skills and the ability to investigate complex behavior using SQL or other query languages.
• Familiarity with cloud infrastructure, SaaS platforms, identity systems, authentication, authorization, and OAuth.
• Understanding of security fundamentals, including identities, permissions, access controls, vulnerabilities, attack techniques, and risk assessment.
• Ability to translate ambiguous security risks into clear threat models, data requirements, and production capabilities.
• Strong engineering judgment across scalability, reliability, security, performance, maintainability, and cost.
• Curiosity and a willingness to rapidly learn unfamiliar AI platforms, APIs, security models, and attack techniques.
• Ability to work independently while collaborating effectively with security researchers, product managers, and engineers.
• Strong written and verbal communication skills in English.

Nice to Have

• Experience building cybersecurity, identity security, SaaS security, threat detection, SIEM, EDR, XDR, or security analytics products.
• Experience researching or developing protections for AI applications, large language models, copilots, or autonomous agents.
• Familiarity with AI security risks such as prompt injection, RAG poisoning, insecure tool use, model abuse, excessive agency, and sensitive-data disclosure.
• Experience with LLM application frameworks, agent protocols, tool integrations, vector databases, or retrieval-augmented generation systems.
• Experience working with SaaS audit logs, identity telemetry, OAuth grants, application configurations, or security events.
• Experience developing detection rules, behavioral analytics, risk models, or attack-path analysis.
• Experience with large-scale streaming or batch-processing technologies.
• Experience using machine learning or generative AI to analyze security data or automate investigations.
• Contributions to security research, open-source projects, technical publications, or responsible vulnerability disclosures.
• Experience collaborating with globally distributed engineering teams.
• Mandarin proficiency.

What Success Looks Like

• Obsidian gains deep, actionable visibility into enterprise AI applications, agents, integrations, identities, permissions, and activities.
• Emerging AI threats are translated quickly into scalable product capabilities and effective detections.
• Customers receive accurate, explainable, and actionable findings about their AI security risks.
• AI security services and data pipelines operate reliably at enterprise scale while maintaining strong cost efficiency.
• Research, product, detection, and engineering teams work through a clear and repeatable process for developing AI security capabilities.
• You help establish Obsidian as a technical leader in securing enterprise AI and agentic systems.

Employee Benefits:

Our competitive benefits packages are designed to support our employees' well-being, both at work and at home. Our US based employees enjoy:

• Competitive compensation with equity and 401k
• Comprehensive healthcare with dental and vision coverage
• Flexible paid time off and paid holiday time off
• 12 weeks of new parent or family leave
• Personal and professional development resources

For more details on our US benefits, or for information on our international benefits, please see here .