Principal Machine Learning Engineer, Agent Harness - Meta Factory

Adobe Unified Platform is building the system that changes how software gets made at Adobe—a platform that understands builders’ intent, breaks down complex work, executes it through autonomous agents, and improves with every cycle. The Meta Factory team is the core of that platform, delivering the Agentic Builders Experience that defines how agents understand goals, decompose work, use tools, evaluate outcomes, and improve over time. This role will shape the technical architecture of the Agent Harness and serve as one of Adobe’s senior technical leaders in agentic systems.

About the role

As a Principal Machine Learning Engineer, you will set the long-term technical direction, solve the hardest design challenges, and establish engineering standards for AI-native software development at Adobe scale. You will work alongside a team of architects to define harness interfaces and standards while balancing performance, cost, and reliability, and lead the evaluation and adoption of emerging trends in agent runtimes and tool-use standards.

Responsibilities

• Work as part of a team of architects shaping the technical direction of the Agent Harness, contributing across agent execution, tool use, context, state, and lifecycle management.
• Define harness interfaces and standards while balancing performance, cost, and reliability.
• Track emerging trends in agent runtimes and tool-use standards and lead their evaluation and adoption at Adobe.
• Define AI-first architecture and engineering standards for agentic systems across Adobe.
• Lead cross-team technical initiatives and provide guidance on complex architectural challenges.
• Advise engineering leadership on emerging agentic execution challenges and mentor senior technical talent across the organization.

Requirements

• 15+ years of software engineering experience, with a strong record of innovation and business impact at Adobe or across the industry.
• Deep expertise in distributed systems, runtime build, and platform architecture, with experience leading large multi-functional initiatives.
• Recognized expertise in agentic systems and LLM infrastructure, with hands-on experience fine-tuning, optimizing, and operating models or runtimes at scale.
• Experience driving AI-first architecture, engineering standards, technology choices, and product direction across organizations.
• Strong communication and influence skills, with the ability to align senior leaders and teams around a shared technical vision.

Pay

U.S. pay range: $206,400 – $379,100 annually. Pay varies by work location and may depend on job-related knowledge, skills, and experience. In California, the pay range for this position is $261,800 – $379,100.