Sr. AI Systems Engineer- Agentic and Productivity Systems
About The Position
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. As we expand into AI-driven workflows across developer productivity and platform initiatives, we are looking for a Senior AI Systems Engineer who operates at the intersection of experimentation and production systems. This role focuses on designing, orchestrating, and operationalizing agent-based systems that improve engineering workflows across CI/CD, developer tooling, and operational diagnostics. This is not a research role and not a prompt-engineering role. This is a systems engineering role focused on building durable infrastructure. You will help build AI-native engineering capabilities that compound engineering velocity across Creative Cloud over time.
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
Nice To Haves
- 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
Responsibilities
- Design and prototype agent-based systems for engineering workflows such as CI diagnostics, code review automation, build failure triage, and autonomous debugging
- Develop multi-agent orchestration patterns with structured state, memory, and control boundaries
- 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
- Develop structured evaluation pipelines including trace-based evaluation and regression testing for agent behavior
- Implement feedback loops and instrumentation that continuously improve AI system performance
- 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
- 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
Benefits
- comprehensive benefits programs
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
