R&D Engineering, Staff Engineer - DevOps (f/m)

Ansys; O Chazo; Presencial; EUR 70.000 - 95.000; Jornada completa

Descripción de la vacante

Synopsys SimAI platform team seeks a seasoned platform engineer to design, deploy, and scale cloud infrastructure using Kubernetes, Pulumi, and Terraform, ensuring reliable AI model training and inference.

You will mentor engineers, improve release processes, and build observability, enabling rapid innovation while maintaining resilience across global deployments.

Formación

• Software development certification.
• Minimum 3 years’ experience managing complex Kubernetes-based platforms.
• Advanced troubleshooting skills.
• Experience designing and operating distributed systems (Kubernetes, Pulumi, NATS, Redis).
• Proficient in Bash and Python or TypeScript.
• Independent and able to own problems end to end from definition through monitoring.

Responsabilidades

• Develop and maintain cloud deployments and scalable platform infrastructure.
• Promote best practices through RFCs and mentoring.
• Scale CI/CD pipelines and release processes.
• Root cause analysis and automated release testing; production incident resolution.
• Design, deploy, and maintain infra with Kubernetes, Pulumi, Terraform.
• Scale compute resources for AI model training and inference workloads.
• Build observability tooling and alerting with Prometheus and Grafana.

Conocimientos

Kubernetes

Troubleshooting

Distributed systems

Python

TypeScript

Bash scripting

Educación

Software development certification

Herramientas

Pulumi

Terraform

NATS

Redis

Descripción del empleo

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 built and scaled platforms that actually run in production, not proof-of-concepts that look good in slides. You know that Kubernetes is powerful, but also that it can become a mess fast if the design decisions are not made with scale and maintainability in mind. When someone says "we need to deploy this new AI service," you do not just spin up a pod and call it done. You ask about traffic patterns, failure modes, and what happens when this thing needs to scale 10x in six months.

What You'll Be Doing

• Perform complex development activities that may require extensive analysis in areas including cloud deployment and maintenance, as well as distributed system maintenance and scaling
• Use best practices and evangelize through RFCs and mentoring
• Help scale our processes (release, development environments, CI/CD pipelines)
• Root cause investigation, automated release testing, production incident solving
• Design, deploy, and maintain the platform infrastructure using Kubernetes, Pulumi, and Terraform
• Scale GPU and CPU compute resources to support AI model training and inference workloads that grow unpredictably
• Build monitoring, alerting, and observability tooling that catches issues before customers do, using tools like Prometheus, Grafana, or equivalent
  

The Impact You Will Have

• Enable Engineers to deploy models that reduce simulation time from hours to minutes, directly accelerating product innovation for Synopsys customers
• Scale the platform to handle growing customer demand without degrading performance or reliability
• Reduce mean time to recovery during incidents by building better observability and automated remediation into the platform
• Improve developer velocity by streamlining deployment workflows and eliminating friction in the release process
• Establish infrastructure patterns and best practices that the broader engineering team can adopt and scale with
• Prevent outages before they happen by designing resilient, self-healing systems that degrade gracefully under load
• Mentor engineers across the organization through RFCs, documentation, and pairing sessions that raise the bar on platform thinking
  

What You'll Need

• Software development certification
• 3 years’ experience, including managing complex platforms that leverage the Kubernetes technology
• Advanced troubleshooting skills
• Distributed systems design and operation experience (Kubernetes, Pulumi, NATS, Redis)
• Proficiency in scripting with Bash and programming in Python or TypeScript
• Comfort working independently and owning problems end to end, from definition through deployment and monitoring
  

Who You Are

• You can explain a complex infrastructure tradeoff to a researcher in two sentences without losing the nuance or talking down to them
• When something breaks in production, you stay calm, gather data, and methodically work the problem instead of guessing and restarting things
• You care about the "why" behind a request, if someone asks for a new service, you ask what problem they are trying to solve before you start provisioning resources
• You are curious enough to test new tools and pragmatic enough to know when the old tool is still the right answer
• You can work across time zones with a distributed team, which means clear written communication and async collaboration are second nature to you
  

The Team You’ll Be Part Of

The SimAI platform is a SaaS-based platform that brings unprecedented speed, innovation, and accessibility to simulation. It is based on proprietary Deep learning algorithms at the forefront of AI. It empowers users to make faster decisions, faster iterations, and faster innovation. You will collaborate with a team of experts who are, together, building the future of computer-assisted system design.

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.

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