New

Principal AI Systems Engineer

Synopsys
$220000-$330000
United States, California, Sunnyvale
Apr 08, 2026
We Are: At Synopsys, we're transforming IT operations by embedding intelligence into the core of infrastructure systems. From compute clusters to observability stacks, we are building agentic AI capabilities that automate operational tasks, enhance system reliability, and accelerate decision-making. You Are: You are a Principal AI Systems Engineer with strong expertise in enterprise data architecture, Snowflake-based data platforms, backend systems, DevOps practices, and infrastructure reliability, combined with hands-on experience in building and deploying modern AI-powered applications. You enjoy working at the intersection of platform engineering, intelligent systems, and data foundations, building production-grade services that integrate AI capabilities into enterprise infrastructure. You have experience designing scalable APIs, MCP integration layer, platform integrations, and data access patterns that allow AI agents to interact with enterprise systems. You think in terms of reliability, observability, and operational excellence, while also understanding how strong warehouse schemas, curated data models, and governed enterprise data layers are critical to scalable AI systems in large-scale production environments. You also have experience with modern AI technologies such as LLM-based applications, retrieval pipelines, or agent frameworks. You understand how AI systems interact with infrastructure signals and enterprise data, and you are comfortable building services that enable intelligent automation and decision-making. You take ownership of systems end-to-end-from architecture and development to deployment, monitoring, and continuous improvement. You are expected to operate with principal-level technical judgment, influencing architecture and implementation patterns across both platform and data layers beyond your immediate scope. What You'll Be Doing: Design and guide Snowflake-based data architectures, curated data models, semantic data layers, and data access patterns that support AI applications and operational intelligence. Define and review data warehouse schemas, dimensional models, transformation layers, and structured data foundations so AI systems are built on scalable, governable, and consumption-ready enterprise data. 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. Ensure systems are designed for scalability, reliability, and high availability across both cloud and on-prem enterprise environments supporting AI services. Integrate infrastructure signals such as logs, metrics, APIs, and operational data sources into AI Agents and automation. Collaborate with architects, SREs, and platform teams to design reusable infrastructure integrations and platform services that support enterprise automation and AI capabilities. The Impact You Will Have: Drive the transformation of traditional IT operations through intelligent automation and strong data foundations, reducing manual effort and increasing operational efficiency. Shape the next generation of agentic AI services that fundamentally improve infrastructure monitoring, support, optimization, and data-driven decision-making. Contribute to a culture of innovation by collaborating on new architectures, frameworks, and methodologies for AI-powered IT automation. Accelerate incident response and problem resolution by empowering AI agents to analyze, reason, and act on real-time infrastructure data. Enhance visibility and decision-making across compute, cloud, and storage environments with data-driven insights generated by intelligent agents. What You'll Need: 10+ years of experience in data engineering, backend development, infrastructure engineering, platform systems, or data-intensive enterprise systems. Hands-on experience with Snowflake as an enterprise data platform, including schema design, warehouse structures, semantic or curated layers, and performance-aware data architecture decisions. Strong understanding of data warehouse schema design, dimensional modeling, curated data models, and transformation patterns that support analytics, AI, and intelligent systems. Strong expertise in Python and building scalable backend services, APIs, or platform integration layers, with the ability to work effectively across both systems and data workflows. 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. Experience designing structured data foundations, data access patterns, and consumption-ready enterprise datasets for downstream AI, observability, and operational use cases. Preferred: Experience integrating infrastructure platforms such as cloud environments, compute clusters, storage systems, or enterprise IT services. Who You Are: A systems-oriented engineer who prioritizes reliability, scalability, operational excellence, and strong enterprise data foundations. Comfortable working across backend development, infrastructure platforms, DevOps environments, enterprise data layers, and warehouse-driven AI architectures. A collaborative engineer who enjoys solving complex system problems alongside architects, SREs, platform teams, and data engineers. Curious about AI systems and interested in applying intelligent capabilities to real operational challenges. Self-directed, organized, and motivated to build durable systems that operate reliably at enterprise scale. The Team You'll Be A Part Of: You'll join a lean, high-impact team operating in startup mode within enterprise IT. Our mission is to build foundational agentic AI capabilities that span compute, cloud, storage, service management, and the supporting enterprise data layer-reshaping how infrastructure is monitored, supported, and optimized at scale. You'll work closely with Principal Engineers, platform teams, SREs, automation experts, and data partners to define and deliver the future of intelligent infrastructure. Rewards and Benefits: We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process. At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability. In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S. Apply Now