Principal AI Architect for Agentic Systems

Adobe Inc.; San Jose (CA); On-site; USD 210,000 - 320,000; Full time

Job summary

Adobe Inc. is seeking a Principal Machine Learning Engineer to define the technical architecture of the Agent Harness and lead Adobe’s senior engineers in agentic systems.

You will set long-term direction, solve complex design challenges, and establish standards for AI-native software at scale. You will work with architects across teams to shape agent execution, tool use, context management, and lifecycle orchestration while balancing performance and cost.

Qualifications

• 15+ years of software engineering with demonstrated impact.
• Deep expertise in distributed systems, runtime build, and platform architecture.
• Experience leading large multi-functional initiatives across organizations.
• Hands-on experience fine-tuning, optimizing, and operating models or runtimes at scale.

Responsibilities

• Shape technical direction of Agent Harness and agentic systems.
• Define harness interfaces and standards balancing performance, cost, and reliability.
• Evaluate and adopt AI runtimes and tool-use standards across Adobe.
• Define AI-first architecture and engineering standards for agentic systems.
• Lead cross-team technical initiatives and mentor senior engineers.

Skills

Distributed systems

LLM infrastructure

AI-first architecture

Architectural leadership

Cross-team collaboration

Job description

Adobe Inc. is seeking a Principal Machine Learning Engineer to define the technical architecture of the Agent Harness and lead Adobe’s senior engineers in agentic systems.

You will set long-term direction, solve complex design challenges, and establish standards for AI-native software at scale. You will work with architects across teams to shape agent execution, tool use, context management, and lifecycle orchestration while balancing performance and cost.