Principal Generative AI & ML Ops Engineer (SME)

Role & responsibilities

• Troubleshoot and resolve AI/ML model, pipeline, and inference issues on GCP Vertex AI.
• Design, deploy, and optimize Generative AI solutions including LLMs, RAG, Conversational AI, and Agent systems.
• Build and manage ML Ops pipelines using Vertex AI, Kubeflow, and MLflow.
• Build and manage ML Ops pipelines using Vertex AI, Kubeflow, and ML flow. workflows.
• Configure and support GKE, Docker, GPU/TPU infrastructure, networking, and IAM.
• Develop and troubleshoot RESTful APIs and gRPC-based AI services.
• Perform root cause analysis (RCA) and drive permanent solutions for production incidents.
• Create technical documentation, reference architectures, and best practice guides.
• Provide technical consulting, onboarding, and architectural guidance to enterprise customers.
• Collaborate with engineering and product teams to improve AI/ML platform capabilities.
• Support 24x7 production operations through rotational shifts.

Preferred candidate profile

• 4+ years of experience in AI/ML, Generative AI, and Google Cloud Platform (GCP).
• Strong expertise in Python, SQL, Machine Learning, Deep Learning, and Large Language Models (LLMs).
• Hands-on experience with Vertex AI, MLOps, Kubeflow, MLflow, Kubernetes (GKE), and Docker.
• Experience building and supporting RAG solutions, Conversational AI, and enterprise AI applications.
• Strong understanding of GPU/TPU infrastructure, model deployment, monitoring, and optimization.
• Excellent troubleshooting, debugging, and root cause analysis skills.
• Strong communication and stakeholder management abilities with customer-facing experience.
• GCP certifications and experience in cloud-based AI/ML solutions preferred.
• Willingness to work in a 24x7 rotational support environment.