Staff Security Engineer

Quanata

. Secure AI-enabled products, internal applications, APIs, services, and platforms throughout their lifecycle .

Posted 9/22/2026full-timeRemote • United StatesLead💰 $235,000 - $305,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in securing AI-enabled products and cloud-native environments, with a strong focus on threat modeling, security architecture, and risk assessments. Proficient in developing security standards and collaborating across teams to enhance security practices and incident response capabilities.

Highest-signal resume keywords

Full-Stack SecurityCloud SecurityAI Security RisksAWS Security PracticesDevSecOps

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Threat ModelingSecurity Architecture ReviewsRisk AssessmentsInfrastructure-As-CodeContainer SecurityCI/CD PipelinesSecure Design ReviewsCode ReviewsData Leakage PreventionAI-Enabled Application Security

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationIndependent WorkPrioritizationCross-Functional Leadership

Tools & Technologies

AWSSaaS PlatformsAPIsDeveloper ToolsMonitoring ToolsLogging ToolsIncident Response ToolsSecrets Management ToolsWorkload Identity SolutionsDeployment Automation Tools

Industry Keywords

CybersecurityAI-Enabled ProductsMachine LearningGenAISecurity OperationsVulnerability ManagementGRCOperational RisksSoftware Supply ChainSecurity-By-Design

Tech Stack

Tools & technologies

AWSCloudCyber Security

About the role

Key responsibilities & impact

Secure AI-enabled products, internal applications, APIs, services, and platforms throughout their lifecycle
Lead threat modeling, security architecture reviews, and risk assessments for LLM applications, RAG pipelines, agentic workflows, MCP servers, model providers, third-party AI tools, plugins, automations, and AI-assisted development
Define and implement secure AI engineering patterns, guardrails, standards, and reference architectures
Strengthen AWS-native infrastructure and CI/CD environments, including infrastructure-as-code, containerized workloads, secrets management, workload identity, deployment pipelines, and software supply chain controls
Partner with security operations, detection engineering, incident response, and vulnerability management teams to improve AI-related detection, observability, telemetry, and response capabilities
Evaluate AI applications, SaaS platforms, model providers, MCPs, agents, developer tools, and third-party technologies for security, privacy, access, data exposure, logging, contractual, and operational risks
Develop security guidance, training, and enablement materials for engineering and business teams
Lead cross-functional security-by-design initiatives, translate security objectives into technical requirements, influence architectural decisions, and own broader security projects and critical incident response efforts

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Cybersecurity, Engineering, Information Systems, or a related technical field; an equivalent combination of education and relevant experience; or equivalent relevant experience
8+ years of experience in full-stack security, product security, application security, cloud security, DevSecOps, infrastructure security, or software engineering with significant security responsibilities
5+ years of demonstrated experience working with AI, machine learning, LLM, GenAI, or AI-enabled application environments
Experience conducting security architecture reviews, threat modeling, secure design reviews, code or configuration reviews, and risk assessments
Experience evaluating and securing third-party SaaS platforms, AI tools, model providers, developer tools, APIs, integrations, and vendor-managed services
Experience partnering across security operations, detection engineering, incident response, GRC, privacy, infrastructure, and product engineering teams
Strong hands-on experience securing cloud-native environments, preferably AWS, including IAM, networking, logging, monitoring, secrets management, workload identity, infrastructure-as-code, and secure deployment practices
Strong understanding of CI/CD pipelines, source control, build systems, artifact management, deployment automation, container security, software delivery workflows, and software supply chain risk
Working knowledge of AI-specific security risks, including prompt injection, insecure tool use, excessive agency, data leakage, RAG security risks, plugin and MCP risks, insecure agent permissions, model extraction, model abuse, and AI supply chain concerns
Ability to translate AI and cloud security risks into engineering requirements, controls, standards, detections, and operational procedures
Strong written and verbal communication skills
Ability to work independently, prioritize competing risks, and lead complex cross-functional security initiatives

Benefits

Comp & perks

Medical, dental, and vision insurance
Life insurance and supplemental income plans for employees and dependents
Headspace app subscription
Monthly wellness allowance
401(k) plan with company match
One-time $2,000 payment for in-home office equipment and furniture
Fully provisioned MacBook Pro
Four weeks of PTO in the first year
Twelve weeks of fully paid parental leave for birthing and non-birthing parents
Up to $5,000 annually for professional learning, continuing education, and career development
LinkedIn Learning subscriptions
Coaching opportunities through BetterUp
Remote-first work arrangement
Occasional travel may be requested or encouraged but is not required
Core meeting hours from 9AM–2PM Pacific time