About the job
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.
Responsibilities
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.
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.
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.
Embed privacy-by-design and compliance requirements (data governance, consent, data residency, retention) directly into the agent architecture; partner with Legal/Privacy to keep architecture decisions ahead of regulatory expectations.
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.
Serve as Adobe's senior technical authority and encouraging leader on secure agentic AI architecture; mentor senior engineers and architects and elevate security and privacy proficiency across the broader engineering organization.
Qualifications
Minimum
20+ years of experience in software engineering or security architecture, with a strong focus on distributed systems, platform engineering, and enterprise-scale access control.
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
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.