Principal Architect — Distributed Systems & Agentic AI Security, Governance

Summary

At Adobe, we are building enterprise-grade Agentic-AI systems that automate large-scale data access and workflow execution for business processes. These systems not only embody foundational enterprise security and privacy considerations but also provide robust and safety-preserving capabilities in the emerging world of agent identity, delegated access control and human-in-the-loop execution models.

This is a multi-fluency role: you need the distributed systems and Agentic-AI depth to architect how agents reason, plan, and act at scale, and the security-and-compliance mechanisms that manage safe and trustworthy execution. You will partner with engineering, product, legal/privacy, and security leadership to turn fast-moving agentic AI capabilities into a governed, enterprise-ready platform.

Key Responsibilities

Agentic AI Architecture

• Define and drive the end-to-end reference architecture for how AI agents are authenticated and authorized to access enterprise data, tools, and systems across Adobe's Customer Experience Platform — covering agent lifecycle management, interaction protocols, memory/context handling, and action-execution frameworks.

• Evaluate and select frameworks, protocols, and platforms (e.g., agentic orchestration frameworks, MCP-style tool systems, policy engines such as OPA/Cedar-class authorization) that best support secure, governed multi-agent systems at Adobe's scale.

Security, Compliance & Privacy by Design

• Own the security architecture for agent-to-system and agent-to-agent interactions: identity and workload authentication, least-privilege authorization, secrets and credential mediation, network egress controls, runtime isolation, and telemetry/audit evidence sufficient to satisfy internal audit and external regulators.

• Embed privacy-by-design and compliance requirements (data governance, consent, data residency, retention) directly into the agent architecture rather than bolting them on after the fact; partner with Legal/Privacy to keep architecture decisions ahead of regulatory expectations for autonomous AI systems.

Cross-Organizational Leadership & Standards

• Lead architectural reviews and set standards for scalability, resiliency, observability, and cost efficiency — with security and compliance treated as first-class, non-negotiable design constraints rather than downstream signoffs.

• Contribute to or lead an Architecture Review Board function for agentic AI, ensuring new capabilities are evaluated consistently against Adobe's governance bar before they ship.

Technical Leadership, Mentorship & Evangelism

• Serve as Adobe's senior technical authority and encouraging leader on secure agentic AI architecture. Mentor senior engineers and architects. Elevate security and privacy proficiency across the broader engineering organization.

• Create and maintain architecture documentation, decision records, and threat models that are equally useful to implementation teams and to senior leadership.

Executive & Customer Engagement

• Represent Adobe's agentic AI security and governance posture to executive leadership, enterprise customers, and — where relevant — regulators and standards bodies, with clear, bounded claims about maturity, open risks, and the evidence required before broader rollout.

• Provide thought leadership across the organization where agentic AI access governance is heading, and shape Adobe's roadmap accordingly.

Basic Qualifications

• 15+ years of experience in software engineering and security architecture, with a strong focus on distributed systems, platform engineering, and enterprise-scale access control. Recent experience in Agentic AI Security

• Deep understanding of agentic AI architecture patterns: agent orchestration, tool/function calling, reasoning and planning loops, and multi-agent coordination, along with the risks specific to each.

• Expert-level knowledge of identity and access management, authorization models, and credential/secrets management (e.g., OAuth/OIDC, SAML, workload identity, policy-as-code approaches such as OPA/Rego or Cedar-class engines).

• Demonstrated ability to lead ambiguous initiatives involving multiple functions across security, product, legal/privacy, and infrastructure teams, and to influence org-wide standards without direct authority.

Preferred Qualifications

• Practical experience with agent-lifecycle governance, including audit evidence generation and anomaly/incident response for autonomous systems.

• Familiarity with privacy and compliance frameworks relevant to AI systems (e.g., data residency, consent management, and sectoral regulatory expectations for automated decision-making).

• Experience building or governing developer platforms, cloud-native services, or streaming data platforms (e.g., Kafka, Spark) at enterprise scale.

• Advanced degree (M.S. or Ph.D.) in Computer Science, Security, or related technical field.

• Experience standing up or contributing to an enterprise Architecture Review Board or equivalent governance function.

Success Profile

• Strong systems thinker who can simplify genuinely hard problems — you make governance transparent without making it burdensome.

• Comfortable operating at both hands-on technical depth and strategic, executive-facing leadership.

• High ownership, high bias for execution, and a track record of turning a working draft into a production-grade, adopted standard.