AI Infrastructure Engineer - GoLang, Kubernetes, Dockers, Linux - 8-12 years

Meet the Team We are an innovation team on a mission to transform how enterprises harness AI. Operating with the agility of a startup and the focus of an incubator, we’re building a tight-knit group of AI and infrastructure experts driven by bold ideas and a shared goal: to rethink systems from the ground up and deliver breakthrough solutions that redefine what's possible — faster, leaner, and smarter.

We thrive in a fast-paced, experimentation-rich environment where new technologies aren’t just welcome — they’re expected. Here, you'll work side-by-side with seasoned engineers, architects, and thinkers to craft the kind of iconic products that can reshape industries and unlock entirely new models of operation for the enterprise.

If you're energized by the challenge of solving hard problems, love working at the edge of what's possible, and want to help shape the future of AI infrastructure — we'd love to meet you.

Impact Cisco is seeking an experienced and innovative Control Plane Engineer to develop the control plane for the next-generation AI infrastructure. This role focuses on designing and implementing scalable, reliable, and efficient control plane components to manage AI workloads. The ideal candidate will have a strong background in microservices architecture, Kubernetes, and distributed systems, along with expertise in modern programming languages and cloud-native technologies.

As AI Control Plane Engineer your work will have a significant impact on:

• Enabling seamless orchestration and management of AI workloads across distributed environments.
• Improving the reliability, scalability, and performance of AI control plane services.
• Ensuring operational simplicity and ease of debugging for control plane services.
• Driving innovation in control plane architecture to improve efficiency and performance of AI infrastructure.

Your contributions will empower Cisco to deliver best-in-class AI infrastructure solutions and help customers scale AI workloads with confidence.

Key Responsibilities

• Design and implement control plane components using Golang AND Python,
• Leverage Kubernetes (K8s) concepts, CRDs, and operator patterns (e.g., Kubebuilder) to build control plane services.
• Develop scalable and highly available (HA) microservices that span across regions, ensuring reliability at scale.
• Build and maintain GRPC, REST APIs, and CLI tools for seamless integration and control of AI infrastructure.
• Address operational challenges of running applications as SaaS, focusing on ease of deployment and lifecycle management.
• Establish and follow best practices for release management, including CI/CD pipelines and version control hygiene.
• Design and implement strategies for live upgrades to minimize downtime and ensure service continuity.
• Develop and implement telemetry collection mechanisms using eBPF and other tools to provide insights into system performance and health.
• Define and monitor SLA/SLO metrics to ensure the reliability of control plane services.
• Design and manage stateful applications, ensuring high performance and reliability of underlying databases.
• Build systems with debuggability in mind, simplifying troubleshooting and remediation for operational teams.
• Collaborate with other teams to ensure control plane compatibility with GPU/CUDA-related technologies.

Minimum Qualifications

• Proficiency in Golang and Python.
• Strong expertise in Kubernetes (K8s), including CRDs, the operator pattern, and tools like Kubebuilder and Helm.
• Experience with API design and implementation (GRPC, REST APIs, and CLI).
• Proven track record in designing and scaling highly available microservices across regions. Strong understanding of distributed systems architecture and fundamentals.
• Familiarity with telemetry tools and SLA/SLO monitoring for large-scale systems.
• Strong debugging skills and experience building systems with easy remediation capabilities.
• Passion for learning and staying updated on the latest trends in AI infrastructure and cloud-native technologies.
• Bachelor’s degree+ and relevant 7+ years of Engineering work experience.

Preferred Qualifications

• Proficiency in programming languages such as C++, Golang.
• Hands-on experience with eBPF for collecting insights and optimizing system performance.
• Knowledge of GPU/CUDA technologies and their integration into infrastructure systems.
• Knowledge of release management best practices, including versioning and rollback mechanisms.
• Familiarity with SaaS operational models and challenges.

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.