# Principal AI Systems Engineer

**Company**: Synopsys
**Location**: Sunnyvale, California
**Work arrangement**: onsite
**Experience**: senior
**Job type**: Employee
**Salary**: $191,000-$286,000
**Category**: Engineering
**Industry**: Technology
**Ticker**: SNPS
**Wikidata**: https://www.wikidata.org/wiki/Q2303478

**Apply**: https://careers.synopsys.com/job/sunnyvale/principal-ai-systems-engineer/44408/92433698208
**Canonical**: https://yubhub.co/jobs/job_f9cca57a-37d

## Description

We are seeking a Principal AI Systems Engineer to join our team. As a Principal AI Systems Engineer, you will be responsible for designing and implementing the MCP integration layer, building scalable backend services, and developing and maintaining production-grade DevOps pipelines.

## What you'll do

- Design and implement the MCP integration layer, including MCP registry services and MCP endpoints, enabling AI systems and agents to securely discover and interact with enterprise infrastructure tools and platforms.

- Build scalable backend services leveraging expertise in Python that power automation systems, enterprise infrastructure integrations, and AI-driven operational workflows.

- Develop and maintain production-grade DevOps pipelines, including CI/CD workflows, containerized deployments, monitoring, and reliability automation.

## What you need

- 10+ years of experience in software engineering, backend development, infrastructure engineering, or platform systems.

- Strong expertise in Python and building scalable backend services, APIs, or platform integration layers.

- Experience designing MCP registry services, MCP endpoints, or similar service discovery and integration layers connecting enterprise systems.

- Strong DevOps experience, including CI/CD pipelines, containerization (Docker/Kubernetes), infrastructure automation, monitoring, and reliability practices.

- Hands-on familiarity with modern AI systems including LLM-based services, RAG architectures, or agent frameworks.

## Skills

### Required
- Python
- backend development
- infrastructure engineering
- DevOps

### Nice to have
- LLM-based services
- RAG architectures
- agent frameworks