Sr Security Engineer - AI

Quickbase is on a mission to eliminate Gray Work through its Dynamic Work Management platform, empowering organizations to improve productivity and reduce costs. The Senior AI Security Engineer will be a key contributor to the AI security program, responsible for securing enterprise AI technologies and supporting AI governance initiatives. This role requires collaboration with various teams to implement security controls and evaluate emerging AI technologies.

Responsibilities:

• Serve as the Security team's primary point of contact for enterprise AI technologies and internal AI adoption initiatives
• Evaluate and secure the use of AI solutions across corporate functions including Engineering, Product, IT, Finance, HR, Customer Success, Sales, Marketing, and Legal
• Assess security, privacy, compliance, and data protection risks associated with AI tools, AI assistants, copilots, AI agents, and AI-enabled business workflows
• Review AI integrations involving enterprise platforms such as GitHub, Salesforce, Slack, Jira, Confluence, SharePoint, Workday, ServiceNow, and other business-critical systems
• Define and implement security controls for AI-enabled workflows, enterprise AI deployments, and agent-based automation
• Establish guardrails for the handling of sensitive, confidential, customer, employee, and regulated data within AI environments
• Partner with IT and Security teams to improve visibility into AI usage, AI-related risks, and AI adoption across the organization
• Monitor emerging AI threats, vulnerabilities, and industry developments and recommend appropriate security controls and mitigations
• Partner with Engineering teams to support secure adoption of AI-assisted software development tools and workflows
• Define security guardrails for AI code generation, code review, testing, and developer productivity tools
• Review AI-related engineering use cases and provide practical security recommendations
• Develop standards and best practices for secure AI development
• Support secure integration of AI capabilities into products and engineering workflows
• Evaluate risks associated with AI-generated code, AI agents, model integrations, and developer AI tooling
• Collaborate with Product Security and Engineering teams to embed secure AI practices throughout the software development lifecycle
• Partner with Security, Legal, Privacy, Compliance, and Engineering teams to implement AI governance requirements through technical controls and operational processes
• Participate in AI review boards, architecture reviews, and AI technology assessments
• Conduct AI risk assessments and document security, privacy, compliance, and operational risks
• Support implementation of AI security standards, operational controls, and AI usage guardrails
• Help establish visibility into AI adoption, usage patterns, and AI-related risks across the organization
• Contribute to AI metrics, reporting, and governance maturity initiatives
• Assist with evaluating emerging AI regulations, industry guidance, and evolving best practices
• Identify opportunities to leverage AI to improve security operations, engineering processes, and operational efficiency
• Evaluate emerging AI security technologies and tooling
• Develop automation solutions that improve visibility, governance, and security outcomes
• Support initiatives involving AI agents, workflow automation, and security orchestration
• Partner with Security Operations, IT, and Engineering teams on AI-driven automation opportunities

Requirements:

• 4–7 years of experience in Security Engineering, Application Security, Product Security, Cloud Security, DevSecOps, Information Security, or related cybersecurity disciplines
• Experience conducting security assessments, architecture reviews, technology evaluations, or risk assessments
• Working knowledge of generative AI technologies, large language models (LLMs), AI agents, copilots, and AI-powered development tools
• Understanding of AI security risks including data leakage, prompt injection, excessive permissions, insecure outputs, model misuse, agent abuse, and emerging AI threats
• Experience with cloud platforms such as AWS, Azure, and/or GCP
• Familiarity with modern software development practices, APIs, CI/CD pipelines, and application security principles
• Strong analytical, problem-solving, communication, and stakeholder management skills
• Ability to translate security requirements into practical and scalable solutions
• Experience supporting enterprise AI adoption, AI governance, AI risk management, or AI security initiatives
• Experience with enterprise AI platforms such as ChatGPT Enterprise, Claude Enterprise, GitHub Copilot, Microsoft Copilot, Gemini, or similar technologies
• Familiarity with AI governance frameworks and industry guidance such as NIST AI RMF, ISO 42001, OWASP Top 10 for LLM Applications, MITRE ATLAS, or responsible AI principles
• Experience evaluating AI vendors, AI-enabled SaaS platforms, or emerging technology solutions
• Experience working in SaaS, cloud-native, or high-growth technology organizations