AI Infrastructure Engineer

Job Title: AI Infrastructure Engineer

Location: Pune
Experience: 46 Years
Employment Type: Full-time

Age: 28 yrs(Max)

Job Summary

We are seeking an AI Infrastructure Engineer responsible for designing, building, securing, and operating enterprise-grade AI platforms with a strong focus on cloud- native AI services, Kubernetes, and compliance-driven **infrastructure.**This role will support AI/ML and GenAI workloads using Azure Cognitive Services, Google Vertex AI, Azure Kubernetes Service (AKS), and Virtual Machines, etc ensuring solutions meet regulatory, security, and governance standards critical to the BFSI domain.

Key Responsibilities

AI & Cloud Infrastructure

• Design, deploy, and manage AI/ML infrastructure on Microsoft Azure,
  Amazon Web Service(AWS) and Google Cloud Platform (GCP)
• Build and operate AI workloads using Azure Cognitive Services (Vision,
  Language, Speech, OpenAI, Search)
• Provision and manage Azure Virtual Machines for AI, batch processing, and
  secure workloads
• Architect and maintain AKS-based platforms

Platform Engineering & Kubernetes

• Design and operate AKS clusters with enterprise-grade security, scalability,
  and reliability
• Manage containerized AI workloads using Docker, Helm, and Kubernetes-
  native patterns
• Implement namespace isolation, resource quotas, node pools (including GPU
  nodes), and autoscaling

Compliance, Security & Governance (BFL Critical)

• Ensure AI infrastructure adheres to compliance, regulatory, and audit
  requirements
• Implement identity, access control, encryption, key management, and
  network security
• Enforce data residency, data privacy, and model governance standards
• Support vulnerability management, patching, audit trails, and incident
  response
• Collaborate with Risk, Security, and Compliance teams on AI platform
  controls

Observability & Operations

• Monitor platform health, performance, cost, and capacity (logs, metrics, alerts)
• Optimize cloud and Kubernetes cost for AI workloads (FinOps principles)
• Design for high availability, backup, disaster recovery, and resiliency
• Create operational documentation, runbooks, and standard operating
  procedures

Required Skills & Qualifications
Core Technical Skills

• Strong hands-on experience withMicrosoft Azure (AKS, VMs, Networking,
  Identity)
• Working knowledge of Azure Cognitive Services
• Experience with Google Vertex AI and GCP infrastructure
• Deep understanding of Kubernetes (AKS) and containerized platforms
• Proficiency in Linux, networking, and distributed systems
• Scripting and automation usingPython / Bash

Compliance & Enterprise Skills

• Experience working inregulated environments (BFSI, Finance, Enterprise
  IT)
  • Strong understanding of security, governance, and audit requirements
  • Familiarity with data protection, encryption, IAM, and logging standards

Preferred Qualifications

• Bachelors or master's degree in computer science, Engineering, or related
  field
• Experience with GenAI / LLM infrastructure and enterprise AI platforms
• Knowledge of vertex AI, and hybrid cloud AI architectures
• Certifications such as Azure Administrator, Azure Solutions Architect,
  Kubernetes (CKA/CKAD) would be a Great
• Exposure to Responsible AI frameworks and AI governance

Why Join BFL

• Work onenterprise-scale AI platforms in a highly regulated environment
• Opportunity to build secure, compliant, and production-ready AI
  infrastructure
• High-impact role supporting BFL’s AI and digital transformation initiatives
• Strong focus on governance, reliability, and operational excellence