We Are
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 Are
You have spent years building platforms that bridge simulation, AI, and modern web architecture, and you have learned that the hardest part is not making it work once but making it scale, stay secure, and actually get adopted by engineers who have real deadlines. You think in systems, not features. You know the difference between a prototype that impresses in a demo and a production platform that runs reliably at 3 a.m. when someone in Germany needs results, and you care deeply about that difference.
You are comfortable sitting with a customer team trying to automate simulation workflows and walking out with an architecture that integrates PyAnsys services, containerized deployments, and MLOps pipelines without creating a maintenance nightmare. You do not wait for perfect specs. You ask the right questions, align stakeholders, and build something that works today and evolves tomorrow.
You have a point of view on what good platform engineering looks like. You push back when an architecture is too fragile or a deployment strategy ignores observability. You are technical enough to debug a Kubernetes networking issue and strategic enough to influence product roadmaps. At Ansys, you will work on platforms that help engineering teams solve problems that matter, and the solutions you build will shape how simulation and AI come together in production.
What You'll Be Doing
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Architect and lead development of scalable, cloud-native application platforms that integrate Ansys simulation technologies with modern web, API, and AI capabilities, owning decisions across frontend, backend, data layers, and infrastructure
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Design and implement end-to-end DevOps frameworks using infrastructure as code, CI/CD pipelines, Docker, and Kubernetes to enable automated, repeatable, and reliable deployments
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Develop and integrate Python-based servicesand PyAnsys into distributed, service-oriented architectures that enable advanced automation and simulation-driven workflows
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Lead MLOps adoption by building model packaging, deployment, monitoring, and lifecycle management workflows that bring AI into engineering tools without breaking production
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Establish observability best practices including logging, monitoring, alerting, and performance tuning across distributed systems and ML services
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Partner with customers, internal engineering teams, and product development to define solution architectures,validatenew capabilities, and influence long-term technology roadmaps
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Mentor engineers on full stack development, DevOps,MLOps, and architectural best practices while leading strategic initiatives and reusable platform frameworks
The Impact You Will Have
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Enable engineering teams to run simulation workflows at scale with platforms that are secure, maintainable, and built for production, not just proof of concept
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Accelerate customer innovation by integrating AI and ML capabilities directly into engineering workflows, reducing manualeffortand increasing delivery velocity
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Shape how Ansys simulation technologies are deployed and consumed in cloud-native, containerized environments across diverse customer use cases
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Reduce deployment friction and operational risk byestablishingautomated CI/CD pipelines and infrastructure as code practices that teams can rely on
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Influence product strategy by translating real customer challenges into technical requirements that drive platform evolution and new capabilities
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Build reusable frameworks and architectural patterns that raise the bar for how application platforms are designed and delivered across the organization
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Create a culture of technical excellence by mentoring engineers, sharing knowledge through workshops and content, anddemonstratingwhat good looks like in practice
What You'll Need
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Bachelor's degree, Master's, or PhD in Mechanical, Chemical, Aerospace, or Electrical Engineering, Computer Science, Mathematics, or a related field
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Required minimum years of professional experience in an engineering software environment: BS+12, MS+10, or PhD+7
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Proventrack recorddesigning and leading development of scalable, production-grade web applications across frontend, backend, and API layers
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Strong hands-onexpertisein cloud-native architectures including Docker, Kubernetes, and CI/CD pipelines, withdemonstratedimplementation of DevOps practices like infrastructure as code and automated deployments
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Strong proficiency in Python for building services, automation scripts, and integrating with scientific or engineering libraries is a strong plus
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Practical experience withMLOpsworkflows including model integration, lifecycle management, reproducibility, and production deployment of ML services
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Experienceworking in cross-functional, customer-facing environments where you translated business and engineering requirements into scalable technical solutions
Who You Are
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You can walk into a room with a customer engineering team, listen to their workflow pain points, and walk out with an architecture sketch that solves the real problem without overengineering it
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You debug with purpose, whether it is a Kubernetes networking issue, a slow API endpoint, or a model deployment that fails silently, you know how to isolate the problem and fix it without creating three new ones
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You mentor by showing, not telling, pairing with engineers to work through a tough architectural decision or a tricky CI/CD pipeline setup, and leaving them better equipped to handle the next one
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You push back when something does not make sense, whether it is a deployment strategy that ignores security, an architecture that will not scale, or a timeline that skips observability
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You communicate across contexts, explaining a complex tradeoff to a VP in two sentences, walking a junior engineer through a design pattern, or writing documentation that someone willactually readsix months from now
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You stay current without chasing hype, you know which tools and practices are ready for production and which ones are still too early, and you make decisions that balance innovation with reliability
The Team You'll Be Part Of
You will join the Ansys Customer Excellence team, working at the intersection of engineering simulation, modern software platforms, and AI-enabled solutions. This is a technical leadership role where you will collaborate with customers, internal product teams, and engineers across geographies to shape how simulation technologies are integrated into scalable, cloud-native platforms. Your recruiter will share more about the team structure, current initiatives, and collaboration model during the interview process.
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.
