Enterprise Security Software Architect; AI​/ML

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Job Category:
Software Engineering

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

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We're Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too - driving your performance and career growth, charting new paths, and improving the state of the world.

If you believe in business as the greatest platform for change and in companies doing well and doing good - you've come to the right place.

The Enterprise Security team builds and operates highly scalable, fault-tolerant, distributed systems to deliver cloud-scale security services. Our key investments span Identity and Access Management, Identity Intelligence, and Security Data Platforms, where we design and implement consistent, scalable, and data-driven security services across Salesforce Enterprise. We integrate our IT network, public cloud infrastructure, and data centers, while increasingly leveraging AI/ML-driven insights to detect risk, automate decisions, and continuously adapt access controls-empowering engineers to operate securely at global scale.

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.

• 15+ years of software development experience.
• 7+ years designing and…