Senior Staff AI Security Lead
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Job Description
Senior Staff AI Security Lead building secure LLM infrastructure and driving AI adoption across IonQ’s quantum computing security organization. Delivering production AI systems, governance, and measurable analyst productivity gains.
Responsibilities:
- Build a shared enterprise AI platform with model gateway and routing, authentication and authorization, secrets handling, rate limiting, cost attribution, and audit logging
- Establish reusable patterns for agentic workflows, including tool and MCP server integration, sandboxed execution, human-in-the-loop approval gates, and least-privilege agent credentials
- Connect security knowledge to AI systems through governed retrieval pipelines with access controls and data classification enforcement
- Build evaluation harnesses, regression suites, and observability for output quality, latency, cost, hallucination rate, and drift
- Implement guardrails against prompt injection, model-output data exfiltration, insecure tool use, and AI supply-chain risk
- Own reference architecture, golden paths, and internal documentation
- Identify high-value AI use cases across detection engineering, incident response, threat intelligence, vulnerability management, GRC, and security operations
- Deliver high-visibility AI applications that improve analyst productivity
- Run office hours, workshops, documentation, prompt and agent design sessions, and brown-bags
- Define and report adoption and impact metrics
- Partner with Legal, Privacy, and Compliance on acceptable-use policies, review processes, and AI risk frameworks
- Evaluate vendors and open models and maintain the security organization’s AI point of view
- Report to the security leadership team and collaborate with Platform Engineering, IT, Legal, Privacy, and AI/ML
- Travel up to 10%
Requirements:
- 8+ years in security engineering, platform engineering, or a closely related technical field, including significant hands-on software development
- Demonstrated experience building and operating production systems with large language models
- Strong software engineering fundamentals and fluency in Python or an equivalent language
- Experience with API design, distributed systems, and cloud infrastructure (AWS, GCP, or Azure)
- Deep understanding of identity and access management, secrets management, network boundaries, logging and detection, and secure software development practices
- Working knowledge of AI-specific risks and practical mitigations
- Track record of driving technical change through influence rather than authority
- Clear written and verbal communication
- Sound judgment about where AI is genuinely useful
- Experience with agent frameworks, orchestration, and MCP or comparable tool-use standards
- Experience building evaluation frameworks or LLM observability tooling
- Background in security operations, detection engineering, or incident response
- Experience with retrieval systems, embeddings, vector databases, and knowledge pipeline design
- Familiarity with NIST AI RMF, ISO/IEC 42001, or OWASP Top 10 for LLM Applications
- Experience fine-tuning or evaluating open-weight models
- Prior experience as a first or founding hire on a platform or capability that later scaled organization-wide
- For US technical jobs, employment is contingent on verifying U.S. Person status, obtaining a necessary license, or confirming a license exception for export controls and government contracts work
Benefits:
- Bonus
- Equity
- Comprehensive medical, dental, and vision plans
- Matching 401(k)
- Unlimited PTO
- Paid holidays
- Parental/adoption leave
- Legal insurance
- Home technology stipend
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