Principal AI Systems Engineer- Agentic and Productivity Systems

About the role

The Creative Cloud Engineering organization is building the next generation of AI-powered engineering infrastructure to accelerate developer productivity and operational excellence across the Creative Cloud ecosystem. This role focuses on designing, orchestrating, and operationalizing agent-based systems that improve engineering workflows across CI/CD, developer tooling, and operational diagnostics.

Responsibilities

• Agentic Workflow Development
• Design and prototype agent-based systems for engineering workflows such as CI diagnostics, code review automation, build failure triage, and autonomous debugging
• Rapidly evaluate emerging AI frameworks, agent tooling, and developer AI platforms in real-world engineering environments
• Build reusable orchestration layers and service architectures for AI-powered engineering systems
• Implement feedback loops and instrumentation that continuously improve AI system performance
• Production Hardening
• Convert experimental workflows into secure, scalable, production-grade services
• Implement observability, tracing, cost controls, and model routing
• Ensure reliability, operational stability, and measurable impact of AI-powered systems
• Platform Strategy & Collaboration
• Define internal standards for AI experimentation, evaluation, deployment, and monitoring
• Partner with DevEx, CI/CD, and platform teams across Creative Cloud to embed AI-native capabilities
• Build cohesive infrastructure that prevents tool sprawl and enables reusable AI productivity systems across teams

Requirements

• 8+ years of software engineering experience, with demonstrated depth in systems-level work
• Strong systems engineering experience (Python, Go, TypeScript, or similar)
• Experience building distributed systems, developer platforms, or infrastructure services
• Experience integrating LLMs or AI APIs into production systems
• Experience evaluating and integrating across multiple AI providers (e.g., AWS Bedrock, Anthropic, OpenAI) including cost optimization and capacity planning
• Strong understanding of observability, metrics, logging, and tracing systems
• Experience operating production services at scale

Qualifications

• Experience with agent frameworks (LangGraph, AutoGen, CrewAI, or similar)
• Experience with embeddings, vector databases, or RAG architectures
• Experience designing evaluation and benchmarking systems for AI workflows
• Experience with CI/CD platforms, developer tooling, or build systems
• Experience building internal developer productivity platforms
• Familiarity with cost-aware model orchestration and multi-model routing

Preferred Qualifications

• Experience with AI Use Guidelines for Interviews

Pay

$190,200 -- $360,500 annually