Bengaluru, Karnataka
Job Summary
Job Title: AI Platform Engineer / Architect
Job Summary
We are looking for experienced AI Platform Engineers / Architects with deep expertise in designing and building enterprise-grade AI platforms on Cloud (Azure) environments. The role focuses on establishing scalable, secure, and governed AI/GenAI ecosystems—covering model usage, agentic systems, platform engineering, and operational excellence. The ideal candidate will drive platform standardization, enable self-service AI capabilities, and ensure compliance with emerging AI regulations.
Key Responsibilities
Key Responsibilities
Define and implement zero-trust identity architecture for AI platforms (Identity & RBAC)
Architect and establish enterprise landing zones within Azure environments
Develop and govern AI/LLM model usage strategy and lifecycle frameworks
Standardize and implement prompt engineering frameworks and best practices
Design enterprise knowledge architectures leveraging RAG and vector search
Develop and scale agentic AI systems , including enterprise-grade agent frameworks
Build and manage platform engineering capabilities , including:
Infrastructure as Code (IaC)
Golden paths and standardized productized platforms
Self-service platform pipelines (CI/CD)
Establish GenAIOps / MLOps lifecycle management frameworks for model deployment and monitoring
Define and enforce AI governance and compliance frameworks , aligned with regulations such as the EU AI Act
Drive observability strategy , including monitoring, logging, and FinOps alignment
Define and enforce engineering standards , including best practices in Python and software development
Skill Requirements
Must-Have Skills
Strong expertise in Cloud & Azure Foundations , including Identity & Access Management (IAM), RBAC, networking, and enterprise landing zone design
Deep knowledge of AI / LLM ecosystems , including model strategy, lifecycle management, and governance frameworks
Hands-on experience with prompt engineering frameworks and optimization techniques
Proven experience in RAG-based architectures , including vector search and enterprise knowledge systems
Expertise in designing and implementing agentic AI systems and enterprise agent frameworks
Strong capabilities in platform engineering , including Infrastructure as Code (IaC), CI/CD pipelines, and self-service platform enablement
Experience with MLOps / GenAIOps frameworks , including model lifecycle management, deployment, and governance
Solid understanding of AI security, governance, and compliance , including regulatory frameworks such as the EU AI Act
Experience in observability and operational excellence , including monitoring, logging, and FinOps practices
Strong programming skills in Python and adherence to engineering best practices
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