Job Description Summary

Job Description

Role Summary:

We are seeking a Senior AI Platform Engineer to support the design, scalability, and operational readiness of the BD Intelligence platform on Microsoft Azure. BD Intelligence unifies enterprise AI and digital capabilities into a single, governed hub that creates visibility and enables AI capabilities across BD.

This role works closely with AI engineers, application teams, and Cloud/DevOps partners to ensure the platform is secure, resilient, and production‑ready for AI‑powered services, firewall‑protected cloud environment.

Responsibilities:

• Partner with AI engineering and Cloud/DevOps teams to define and align platform deployment patterns, CI/CD standards, and operational practices.
• Support the design and evolution of Azure architectures for AI platforms, including:
  • App Services, Azure Kubernetes Service (AKS), Azure Container Apps, Azure Web Apps
  • Azure Virtual Networks, Private Endpoints, Azure Private Link, Azure AD integration
  • Data services such as Azure Blob Storage, Azure SQL Database, and PostgreSQL
• Review and guide Infrastructure‑as‑Code (IaC) approaches to ensure alignment with BD infrastructure and platform standards.
• Ensure alignment with security, identity, and network controls, including VPN access models, RBAC, private connectivity, and BD enterprise security requirements.
• Collaborate with platform and SRE teams to support observability and monitoring strategies using Azure Monitor, App Insights, Log Analytics, and related tooling.
• Drive operational readiness for AI services, including scalability, availability, resiliency, and performance considerations.
• Support onboarding and lifecycle management of AI products and services onto the BD Intelligence platform.
• Maintain platform documentation, solution architectures (HLD/LLD), operational runbooks, and access models.
• Support controlled scaling and production deployment of AI‑powered digital tools hosted on the platform.

Required Skills:

• Experience supporting AI/ML or data platforms in enterprise environments.
• Strong understanding of Azure cloud architecture and DevOps principles.
• Familiarity with:
  • CI/CD pipelines and deployment strategies
  • Containerized platforms and Kubernetes concepts
  • Private networking, identity, and security architectures on Azure
• Ability to translate AI platform needs into clear technical, security, and operational requirements.
• Strong collaboration and communication skills across engineering and infrastructure teams.

Preferred Qualifications:

• Experience supporting or scaling AI/ML services, including performance‑sensitive or GPU‑enabled workloads.
• Familiarity with Python‑based AI service architectures (e.g., FastAPI).
• Exposure to Azure‑native AI/ML services from a platform or operations perspective.

Required Skills

Optional Skills

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