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.