Senior Staff AI Security Lead

IonQ

. Build a shared enterprise AI platform with model gateway and routing, authentication and authorization, secrets handling, rate limiting, cost attribution, and audit logging .

Posted 10/6/2026full-timeRemote • United StatesSenior💰 $180,000 - $225,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and operating AI platforms with a focus on security, including model gateway integration, access controls, and observability. Proficient in software engineering, particularly with Python, and experienced in managing AI-specific risks and compliance frameworks.

Highest-signal resume keywords

Security EngineeringPython ProgrammingAPI DesignAI Risk ManagementCloud Infrastructure

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Software DevelopmentLarge Language ModelsIdentity and Access ManagementSecrets ManagementDistributed SystemsEvaluation FrameworksRetrieval SystemsAgent FrameworksObservability ToolingNetwork Boundaries

Soft Skills

Clear CommunicationInfluence Without AuthoritySound Judgment

Tools & Technologies

AWSGCPAzureMCPVector Databases

Certifications & Qualifications

NIST AI RMFISO/IEC 42001OWASP Top 10 for LLM Applications

Industry Keywords

Security OperationsDetection EngineeringIncident ResponseComplianceAI Supply-Chain Risk

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Bonus
Equity
Comprehensive medical, dental, and vision plans
Matching 401(k)
Unlimited PTO
Paid holidays
Parental/adoption leave
Legal insurance
Home technology stipend