Principal Generative AI & ML Ops Engineer (SME)

Tata Consultancy Services; Gandhinagar, Indore District, Chennai District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Tata Consultancy Services is seeking an AI/ML Engineer to troubleshoot, deploy, and optimize Generative AI solutions on Google Cloud Vertex AI. You will design and maintain ML Ops pipelines, collaborate with product teams, and ensure reliable 24x7 production support.

We value hands-on experience with Vertex AI, Kubeflow, MLflow, Kubernetes (GKE), and Docker, plus deep knowledge of GPUs/TPUs, model deployment, and monitoring. Strong communication skills are essential for customer-facing work.

Qualifications

• 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.

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.

Skills

Python

SQL

Machine Learning

Deep Learning

LLMs

MLOps

Kubeflow

MLflow

Kubernetes (GKE)

Docker

GCP

Vertex AI

Tools

Kubeflow

MLflow

Kubernetes (GKE)

Docker

Vertex AI

Job description

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.