Kubernetes Platform Engineer - AI Infrastructure (8+ Years)

Meet the Team You will be pivotal in contributing to the team responsible for designing and developing the next generation of scalable Kubernetes' infrastructure with machine learning platforms that support both traditional ML and state-of-the-art Large Language Models (LLMs). This is a position for experienced engineers where you will lead the technical direction, ensuring the performance, reliability, and scalability of AI systems while collaborating closely with data scientists, researchers, and other engineering teams.

Your Impact You will take ownership of sophisticated & highly scalable Kubernetes Platforms for microservices workload. Your leadership will be pivotal in driving the adoption and integration of both established Kubernetes platforms and emerging AI/ML technologies. You will mentor junior engineers to reinforce the team’s core technical expertise, ensuring a strong foundation in traditional container orchestration as well as modern AI-driven solutions. This role is ideal for someone passionate about tackling engineering challenges in dynamic environments, with a commitment to delivering scalable, high-impact solutions that blend proven infrastructure methodologies with innovative AI/ML advancements.

Core Responsibilities As a Platform Engineer with AI/ML Experience you will:

• Architect and evolve an enterprise-grade AIOps platform for Kubernetes-based environments.
• Design intelligent agentic frameworks capable of ingesting signals from metrics, logs, events, and external systems
• Define scalable architecture and framework for ML based subsystems for various data intensive tasks like Anomaly Detection, Predictive analysis
• Participate in on-call rotations, contributing to round the clock support, owning production reliability and incident response.
• Build and maintain backend systems and services using Golang and/or Python.
• Drive AIOps initiative across PaaS platforms by collaborating with multi-functional teams, including SRE, Software Engineers to operationalize and optimize ML models effectively.
• Experience building or integrating AIOps platforms or intelligent monitoring systems.
• Proficient in Kubernetes (K8) platform to design, develop, and maintain scalable software solutions.
• Exposure to LLM-based agents, RAG systems, or intelligent automation workflows.
• Drive cross-functional collaboration across infrastructure teams to ensure seamless integration and delivery of services.
• Engage directly with clients to gather IT requirements, translate business needs into technical solutions, and architect robust systems.
• Drive technical brainstorming sessions with technical teams to innovate and build effective architectures aligned with client goals.
• Act as a key technical liaison between clients and internal teams, ensuring clear communication and successful project outcomes.
• Provide design, implementation, and operational support for a traditional Kubernetes platform tailored for microservices architecture.
• Enhance and maintain the existing platform to reliably support a large portfolio of business platforms with operation rigor.
• Automate platforms to operate as infrastructure as code, improving efficiency and consistency in platform management.
• Conduct code reviews, establish standard processes, and mentor junior engineers.

Minimum Qualifications / Requirement

• Experience: 8+ years in software/platform engineering with strong exposure to distributed systems.
• Proven expertise in Kubernetes and container platforms (designing, operating, scaling).
• Strong programming skills in Golang and/or Python.
• Hands-on experience building large-scale backend systems and platform services.
• Deep understanding of ML algorithms, data pipelines, and optimization techniques.
• Solid understanding of SRE principles, reliability engineering, and production operations.
• Experience working with data pipelines and time-series systems.
• Demonstrated ability to design end-to-end systems and drive technical strategy.

Preferred Qualifications / Requirements

• Kubernetes and Container Orchestration:
• Expertise in Kubernetes for managing enterprise grade systems and ensuring scalability.
• Experience with Docker and orchestration of complex services.
• Software development: Expertise in Golang or Python
• MLOps Tools and Frameworks: Experience with architecting and optimizing workflows using Kubeflow pipelines, KServe, Airflow, and MLflow.
• Ability to design and implement efficient CI/CD pipelines for ML systems.
• Large Language Models (LLMs): Understanding of LangChain and experience designing RAG systems.
• Knowledge of integrating and scaling vector databases (e.g., Pinecone, FAISS) for real-world applications. 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.