Principal Agentic AI Architect

General Information

Job Title Principal Agentic AI Architect Job ID 9307 City Austin State/Province Texas Date Posted 28-Jan-2025 Job Category Engineering Job Subcategory AI Hire Type Employee Remote Eligible No Base Salary Range: $184000 - $276000

Descriptions & Requirements

Job Description and Requirements

We Are

At Synopsys, we are transforming IT by building intelligent, agentic systems that think, act, and adapt. Supporting some of the world’s most demanding engineering environments—from chip design to high-performance computing—we are reimagining how infrastructure and operations function through the lens of AI.
 
Our team is pioneering the development of agentic IT: AI-powered agents that integrate deeply with infrastructure platforms, observability systems, and automation pipelines. These agents will reshape how issues are detected, resolved, and prevented — enabling faster, smarter, and more autonomous operations across the enterprise.
 
You Are
 
A system-level thinker and AI builder. You are hands-on, curious, and energized by turning advanced machine intelligence into practical automation. You’re comfortable designing intelligent agents that reason and act across complex infrastructure, and you know how to take ideas from prototype to production.
 
You enjoy working across domains — from job telemetry and logs to APIs and orchestration layers — and collaborating with engineering, SRE, and cloud teams to create AI-native workflows that deliver measurable value.
 
What You’ll Be Doing

 

• Architect and develop agentic IT capabilities that enhance infrastructure operations, workload orchestration, and user-facing automation.
• Build LLM-powered agents that integrate reasoning, context-awareness, and real-time data from telemetry and operational sources.
• Design orchestration flows using frameworks like LangGraph, CrewAI, or LangChain, enabling agents to collaborate across tasks and systems.
• Implement grounding strategies using retrieval-augmented generation (RAG) tied to internal documentation, l