Enterprise Security Software Architect, Salesforce

• 15+ years of software development experience
• 7+ years designing and delivering enterprise-scale Security architectures in cloud and hybrid environments
• Demonstrated experience architecting data-intensive, ML-enabled security platforms
• Ability to collaborate with architects, engineering leads, data scientists, and product managers to define long-term architectural vision
• Deep understanding of IAM technologies and protocols:
• IGA, SSO, RBAC/ABAC, PAM, Directory Services
• OAuth2, OIDC, SAML, SCIM, LDAP, CAEP
• Strong grasp of identity lifecycle, entitlement models, SoD, and compliance frameworks (SOX, NIST, CMMC)
• Experience with identity threat detection, continuous access evaluation, 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
• Familiarity with model governance, explainability, drift detection, and bias considerations in security contexts
• Strong coding skills (Java or Go preferred)
• Experience with cloud platforms (AWS preferred)
• Experience with CI/CD pipelines
• Experience with Kubernetes, Docker, Terraform
• Experience with observability and monitoring tools

Desirable

• We are seeking an experienced Security/IAM AI & ML Software Architect to lead the design and evolution of intelligent identity+security platforms powered by data, analytics, and machine learning
• This role will define how AI/ML is embedded into the Enterprise Security Technology stack, spanning identity lifecycle, authentication, access governance, PAM, continuous access evaluation, and identity threat detection
• You will shape a future-ready, zero-trust-aligned security intelligence architecture that scales across a complex hybrid environment and enables proactive, risk-based, and automated access decisions
• You will work closely with Enterprise Security engineering, security data science, platform teams, compliance, infrastructure, and business stakeholders to translate security/identity signals into actionable intelligence and resilient security outcomes
• Architecture & Strategy
• Lead the architectural design for AI/ML enabled IAM capabilities, including:
• Identity lifecycle and access governance
• Risk-adaptive authentication and authorization
• Privileged Access Management (PAM) risk scoring and session analytics
• Identity threat detection and response (ITDR)
• Continuous Access Evaluation (CAE) and policy decisioning
• Define and maintain the Enterprise Identity Intelligence reference architecture, including data flows, ML pipelines, decision engines, and feedback loops
• Align IAM AI/ML strategy with business outcomes, security posture, regulatory requirements, and AI principles
• Data, AI & ML Enablement
• Architect scalable platforms to collect, normalize, enrich, and analyze Security/Identity data, including:
• User, device and non-human identities
• Authentication events, access requests, entitlements, sessions, and behavioral telemetry
• Partner with security data science teams to design, deploy, and operationalize ML models for: Anomaly detection and behavioral baselining, Identity risk scoring and modeling, Privilege misuse and lateral movement detection, Access recommendation, role mining, and policy optimization
• Platform & Engineering Leadership
• Partner with product management and engineering leaders to drive technical roadmaps for the Autonomous IAM platform (API-first, event driven, cloud-native)
• Define architectural guardrails for identity data usage, model governance, explainability, and auditability
• Lead threat modeling and architecture assessments for AI-driven IAM components and their dependencies
• Develop proof of concepts to validate ML feasibility, data quality, and performance at scale
• Integration & Enablement
• Enable IAM administration and onboarding platforms to adopt ML-driven identity standards (for Enterprise Applications)
• Work with enterprise architects and business leaders to map identity intelligence capabilities to user journeys and business processes
• Influence standards for identity APIs, event schemas, feature stores, and policy evaluation frameworks