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TALPRO INDIA PRIVATE LIMITED

AI Platform Engineer (Enterprise AI Infrastructure)

Posted 19 Minutes Ago
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In-Office
Mumbai, Maharashtra, IND
Expert/Leader
In-Office
Mumbai, Maharashtra, IND
Expert/Leader
Build and operate enterprise AI infrastructure for model training, inference, and MLOps. Architect scalable, secure Kubernetes and cloud-native platforms, own system reliability and security, implement CI/CD and observability, optimize AI workloads, and collaborate with AI and product teams to productionize models. The role also drives platform governance, compliance, and infrastructure best practices.
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AI Platform Engineer (Enterprise AI Infrastructure)

Experience: 8–12 Years

Location: Mumbai

Work Mode: Hybrid (3 days/week WFO mandatory)

Engagement: 12 Months C2H

Budget: 22 LPA

Joining: Immediate joiners only


Role Overview

We are seeking a Staff-Level AI Platform Engineer to build and operate enterprise-grade AI infrastructure for production systems. This role focuses on architecting and managing scalable AI platforms across training, inference, and MLOps environments.


The ideal candidate must have deep experience in Kubernetes, cloud-native architectures, CI/CD pipelines, and production AI system reliability.


Key Responsibilities
  • Architect and manage AI infrastructure supporting model training and inference workloads.

  • Build scalable and secure AI platforms for enterprise-grade deployments.

  • Own reliability, availability, scalability, and security of AI systems.

  • Design and implement MLOps pipelines and CI/CD workflows.

  • Optimize Kubernetes-based deployments for AI workloads.

  • Collaborate with AI engineers and product teams to productionize AI models.

  • Implement monitoring, logging, and observability frameworks.

  • Drive platform-level governance, compliance, and infrastructure best practices.

Required Skills

✔ 8–12+ years building and operating enterprise-grade platforms

✔ Strong experience in production AI infrastructure

✔ Deep expertise in Kubernetes

✔ Strong cloud experience (AWS/Azure/GCP)

✔ CI/CD and DevOps practices

✔ Strong Go (preferred) or Python

✔ Experience working with AI coding assistants


Preferred
  • Experience managing distributed AI workloads

  • Experience in large-scale MLOps environments

  • Exposure to AI governance and model lifecycle management



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