Senior AI Platform Engineer

Your Role

As a Senior AI Platform Engineer, you will be responsible for operating, maintaining, and continuously improving the company’s AI platforms running on Kubernetes (On-premise and/or on AWS/GCP) - similar on the AIoEKS (AI on EKS) deployment frameworks and Kubeflow’s Machine Learning Toolkit 

Platform Ownership & Operations 

Deploy new releases and configuration changes through GitOps/DevOps

Monitor platform and service health using logs, metrics, and observability tools   

Improve platform observability, operational tooling/automations, self-service capabilities and reliability practices to reduce recurring issues 

Participate in incident response, root cause analysis and 24x7 operational rotations 

User & Developer Experience  

Investigate & troubleshoot user concerns by either correlating them to system-related issues, breaking integrations and/or user-specific errors/misconfigurations up to recommending/executing resolutions

Advocate for platform standards, security best practices, and operational excellence 

Collaboration and Leadership 

Provide structured Python mentorship to junior engineers, focusing on strong fundamentals and bridge foundational Python knowledge toward MLOps competencies 

Lead the adoption of MLOps best practices for the team 

Influence the team roadmap by identifying gaps in tooling, skills, and processes required to support production-grade AI systems 

Your Qualifications

3+ years of experience supporting production workloads/platforms ( Ray.IO , Jupyter Notebooks, AWS SageMaker, Kubeflow AI Tools or an AI-related equivalent) 

5+ years of hands-on experience AI/ML lifecycle (development/deployment, DevOps/MLOps)

5+ years of Python experience in development & support on AI/ML workflows and data engineering pipelines 

Practically skilled in Kubernetes environments including Cloud-provider managed Kubernetes flavors (AWS-EKS/GCP-GKE)

Knowledge on microservice architectures and service communication patterns 

Strong troubleshooting fundamentals such as application crashes, resource contentions, service latency, and scaling behavior  

Well-rounded competency in analyzing logs, metrics, monitoring systems, and service KPIs  

Plus points if you have:

Exposure in other Data/AI platforms such as Flyte, HuggingFace & AI Agent Platforms (Vertex AI, Claude Code, LangChain, etc...) 

Hands-on experience with automation or scripting (Bash, Python)

Kubernetes or cloud certifications (CKAD, AWS)