AI Platform Architect (Hybrid)

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Work Arrangement: Local candidates preferred

We are seeking a highly experienced Senior AI Platform Architect to provide technical leadership and define the architecture and long-term technical direction for enterprise-scale Generative AI and Agentic AI platforms.

The ideal candidate will combine strong software engineering, cloud infrastructure, distributed systems, and AI/ML platform expertise with the ability to establish architecture standards, influence technology roadmaps, and lead complex cross-functional initiatives.

AI Platform Architecture
Lead architecture and technical strategy for:

Enterprise Generative AI platforms
Agentic AI platforms and agent runtime environments
Model serving infrastructure
Prompt engineering and evaluation frameworks
AI governance, security, and guardrails
AI observability and AI operations
Multi-cloud AI platforms
Scalable and resilient AI infrastructure
Cloud & Platform Architecture
Design and drive enterprise architecture across:

Red Hat OpenShift AI (RHOAI)
Google Cloud Vertex AI
Google Gemini models
Azure AI Foundry
AWS Bedrock
Anthropic Claude
OpenAI platforms and models
Kubernetes and cloud-native infrastructure
API and data platforms
Infrastructure, Scalability & Resiliency
Lead strategic initiatives involving:

Capacity planning and infrastructure optimization
GPU infrastructure and platform strategy
NVIDIA SuperPOD architecture
Multi-region platform architecture
Cloud disaster recovery strategies
Active-active architectures
High availability and fault tolerance
Platform scalability and resiliency
Tier-1 production system architecture

Required Qualifications

10+ years of experience in software engineering, infrastructure engineering, solution architecture, or enterprise architecture.
5+ years designing and implementing large-scale cloud-native platforms.
Strong hands-on experience with:
Kubernetes and/or OpenShift
Distributed systems
Cloud architecture
AI/ML platforms
API platforms
Data platforms
Deep understanding of:
Generative AI
RAG architectures
Agentic AI
Model serving
MLOps
Proven experience designing and supporting highly available, Tier-1 production systems.
Strong understanding of enterprise architecture, scalability, security, resiliency, and performance.
Ability to communicate complex technical concepts effectively to both technical and executive stakeholders.
Demonstrated experience leading cross-functional architecture and engineering initiatives.

Preferred Qualifications

Experience architecting enterprise GenAI or Agentic AI platforms.
Experience with multiple major cloud providers such as AWS, Azure, and Google Cloud Platform.
Experience with GPU infrastructure and NVIDIA platforms.
Experience with AI governance, model evaluation, observability, and responsible AI controls.
Experience developing enterprise technology roadmaps and architecture standards.
Experience leading large-scale cloud transformation or AI platform initiatives.

Key Technologies

AI/ML: Generative AI, RAG, Agentic AI, LLMs, Model Serving, MLOps
Cloud: AWS, Azure, Google Cloud Platform
AI Platforms: OpenShift AI/RHOAI, Vertex AI, Azure AI Foundry, AWS Bedrock
Models: Gemini, Claude, OpenAI
Infrastructure: Kubernetes, OpenShift, NVIDIA GPU/SuperPOD, Distributed Systems
Architecture: Multi-Cloud, Multi-Region, Active-Active, High Availability, Disaster Recovery, Scalability & Resiliency

Ideal Candidate

The ideal candidate is a hands-on enterprise AI architect who can go beyond individual AI applications and design the underlying platform, infrastructure, governance, scalability, and resiliency architecture required to operate GenAI and Agentic AI capabilities at enterprise scale.

Himanshu Goswami

Sr. IT Technical Recruiter

Stellent IT Phone :

Email: Himanshu.goswami
Gtalk: Himanshu.goswami om