Enterprise Security Software Architect (AI/ML)

TL;DR

Enterprise Security Software Architect (AI/ML): Leading the architectural design for AI/ML-enabled Identity and Access Management (IAM) capabilities across a complex hybrid environment with an accent on data flows, ML pipelines, and decision engines. Focus on shaping a zero-trust-aligned security intelligence architecture that scales, detects risk, and automates access decisions.

Location: Bellevue, Washington or San Francisco, California.

Company

hirify.global is a customer company that inspires the future of business with AI, Data, and CRM.

What you will do

• Lead architectural design for AI/ML-enabled IAM capabilities, including identity lifecycle, risk-adaptive authentication, PAM, and identity threat detection.
• Define and maintain Enterprise Identity Intelligence reference architecture, covering data flows, ML pipelines, decision engines, and feedback loops.
• Align IAM AI/ML strategy with business outcomes, security posture, regulatory requirements, and AI principles.
• Architect scalable platforms to collect, normalize, enrich, and analyze Security/Identity data.
• Partner with security data science teams to design, deploy, and operationalize ML models for anomaly detection, risk scoring, and policy optimization.
• Drive technical roadmaps for the Autonomous IAM platform (API-first, event-driven, cloud-native) and define architectural guardrails for identity data usage.

Requirements

• 15+ years of software development experience and 7+ years designing enterprise-scale Security architectures in cloud and hybrid environments.
• Demonstrated experience architecting data-intensive, ML-enabled security platforms.
• Deep understanding of IAM technologies and protocols, including IGA, SSO, RBAC/ABAC, PAM, OAuth2, OIDC, SAML, SCIM, LDAP, CAEP.
• Strong grasp of identity lifecycle, entitlement models, SoD, compliance frameworks (SOX, NIST, CMMC), and zero trust architectures.
• Strong understanding of ML concepts as applied to security, including anomaly detection, classification, and risk scoring.
• Experience designing data pipelines, feature engineering, model inference paths, and feedback loops.
• Strong coding skills (Java or Go preferred) and experience with AWS, CI/CD pipelines, Kubernetes, Docker, and Terraform.

Nice to have

• Hands-on experience with large-scale identity datasets for anomaly detection and real-time policy enforcement.
• Experience architecting risk engines, feature stores, or policy decision services.
• Relevant certifications such as CISSP, CCSP, or TOGAF.

Culture & Benefits

• Work with a team that builds and operates highly scalable, fault-tolerant, distributed systems for cloud-scale security services.
• Opportunity to be a Trailblazer, driving performance and career growth.
• Empower engineers to operate securely at global scale leveraging AI/ML-driven insights.
• Work in an inclusive environment that values equality and is free from discrimination.
• Fair assessment of employees and applicants based on merit, competence, and qualifications.