4 hours ago
Base Salary
$180k - $225k/yr
Responsibilities
- Design and build the enterprise AI platform for 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 approval gates, and least-privilege agent credentials.
- Connect security knowledge sources to AI systems through governed retrieval pipelines with access controls and data classification enforcement.
- Build evaluation harnesses, regression suites, observability, and quality baselines covering output quality, latency, cost, hallucination, and drift.
- Implement guardrails against prompt injection, model-output data exfiltration, insecure tool use, and model and dependency supply-chain risk; red-team the platform and applications.
- Own the reference architecture, golden paths, internal documentation, and standards for security AI development.
- Identify high-value AI use cases across detection engineering, incident response, threat intelligence, vulnerability management, GRC, and security operations.
- Build production AI applications, define adoption and impact metrics, and lead workshops, office hours, documentation, and other enablement programs.
- Partner with Legal, Privacy, and Compliance on acceptable-use policies, review processes, and AI risk frameworks.
- Evaluate vendors and open models and maintain the organization's technical perspective on AI capabilities, security threats, and roadmap implications.
Requirements
- 8+ years in security engineering, platform engineering, or a closely related technical field, including significant hands-on software development.
- Production experience building and operating systems with large language models, including experience handling failures and iterating on deployed systems.
- Strong software engineering fundamentals and fluency in Python or an equivalent language, including API design, distributed systems, and cloud infrastructure.
- Deep understanding of identity and access management, secrets management, network boundaries, logging and detection, and secure software development practices.
- Working knowledge of prompt injection, jailbreaks, model-output data leakage, insecure agent tool use, model supply-chain risk, dependency supply-chain risk, and practical mitigations.
- Track record of driving technical change through influence, consensus-building, teaching, and delivering systems that users adopt.
- Clear written and verbal communication for both technical and executive audiences, along with sound judgment about appropriate AI use.
- Preferred qualifications include experience with agent frameworks, orchestration, MCP or comparable tool-use standards, LLM evaluation or observability tooling, security operations, detection engineering, incident response, retrieval systems, embeddings, vector databases, knowledge pipelines, AI governance, and open-weight model fine-tuning or evaluation.
- Familiarity with the NIST AI Risk Management Framework, ISO/IEC 42001, or the OWASP Top 10 for LLM Applications is preferred.
- Experience as a first or founding hire for a platform or capability that later scaled organization-wide is preferred.
Benefits
- Onsite, hybrid, or fully remote work for the right candidate, with travel up to 10%.
- Comprehensive medical, dental, and vision plans.
- Matching 401(k), unlimited PTO, and paid holidays.
- Parental and adoption leave, legal insurance, and a home technology stipend.
- The total compensation package also includes bonus and equity; participation details are provided with an offer.
Tech Stack
Categories
About IonQ
IonQ builds trapped-ion quantum computers and offers access to them via major cloud platforms and direct systems for enterprise and research users. The public company (NYSE: IONQ), founded in 2015 and headquartered in College Park, Maryland, sells quantum hardware, cloud services, and development tools used in areas like materials modeling, optimization, and machine learning. Its systems are available through AWS Braket, Microsoft Azure Quantum, and Google Cloud Marketplace.