Principal Architect — Distributed Systems & Agentic AI Security, Governance

About the role

Principal Architect — Distributed Systems, Agentic AI, Security, Privacy and 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.

Additional information

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.

AI Use Guidelines for Interviews

Our interviews are designed to reflect your own skills and thinking. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience.

Expected Pay Range

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $190,200 - $360,500 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

In California, the pay range for this position is $248,900 - $360,500

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.