Staff Software Engineer

Synopsys•Sunnyvale, CA

99d•$138,000 - $207,000•Remote

About The Position

Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow. You’re the kind of engineer who enjoys building software that solves real problems and performs reliably in production. You take pride in creating systems that are scalable, thoughtfully designed and built to last. You naturally think beyond the code you write, considering how services fit together and how design decisions impact the broader platform. You value clean architecture, continuous improvement and building solutions that are simple, maintainable and able to evolve as products and teams grow. You thrive in collaborative environments where ownership is encouraged, ideas are openly shared and learning is part of everyday work. When challenges arise, your first instinct is curiosity. You ask thoughtful questions, explore different approaches and work methodically to deliver practical, high-quality solutions. You understand that great software is built through strong communication, teamwork and sound engineering judgement. You’re excited by the opportunities AI is creating for software development and enjoy exploring how modern tools can improve developer productivity and simplify complex workflows. At the same time, you recognize that strong engineering principles and thoughtful design remain the foundation of software built to last. Above all, you’re motivated by building technology that delivers real value and making a meaningful contribution to your team through reliable, scalable and well-crafted software. The Enterprise Storage Engineering team builds and evolves the software platforms that power Synopsys' enterprise-scale storage infrastructure across global sites. Working within a code-first, Kubernetes-native environment, the team focuses on API-driven automation, platform reliability and observability while embracing AI-assisted engineering and intelligent automation. In this role, you'll help design and build backend services that reduce manual effort, improve operational efficiency and enable scalable self-service infrastructure.

Requirements

Strong Python software engineering skills with the ability to write clean, maintainable and well-tested code.
Experience building and supporting production-grade backend services and REST APIs with a focus on reliability, performance and security.
Experience working with Git-based development workflows, code reviews and CI/CD practices that enable safe, repeatable software delivery.
Hands-on experience deploying and operating containerized applications in Kubernetes with confidence troubleshooting across the application stack.
A solid understanding of Linux environments, networking fundamentals and troubleshooting distributed systems.
Experience working with SQL databases and designing scalable, observable and resilient service architectures.
You take ownership of systems from design through production.
You enjoy solving complex engineering challenges in hands-on, collaborative environments.
You’re comfortable working across backend software, infrastructure and AI-enabled automation.
You build solutions that are simple, reliable, scalable and maintainable.
You’re naturally curious and enjoy exploring emerging technologies to solve real-world engineering problems.
You communicate effectively, collaborate openly and contribute to a positive engineering culture.

Nice To Haves

Exposure to enterprise storage, infrastructure automation or AI-assisted engineering workflows including LLMs, tool integrations or agent-based automation would be an advantage.

Responsibilities

Design and deliver backend services and REST APIs that automate enterprise storage and infrastructure workflows.
Build orchestration layers that integrate storage platforms with internal systems, ensuring reliability through retries, idempotency and resilient failure recovery.
Develop, deploy and maintain containerized applications on Kubernetes using modern deployment strategies and environment-specific configurations.
Build and maintain CI/CD pipelines that support automated testing, security validation and reliable software releases.
Enhance system observability by implementing metrics, structured logging and distributed tracing to enable proactive monitoring and faster incident resolution.
Develop AI-assisted operational workflows using LLMs and intelligent tooling to streamline troubleshooting, recommend remediation and reduce manual effort.