Lead AI Platform Architect

Client: Wells Fargo
Location: Bay Area, CA (Preferred) / Charlotte, NC (Secondary)
Work Model: Hybrid
Experience: 10–15 Years
Work Authorization: s, H-1B, and H-4,
Rate: Up to $65/hour on W2

Position Overview

We are looking for a Lead AI Platform Architect with strong hands-on experience designing and building enterprise-scale AI/ML platforms and cloud-native infrastructure.

The ideal candidate must be able to discuss their hands-on project experience in depth, particularly around Kubernetes/OpenShift, AI/ML platforms, MLOps/AI Ops, and cloud architecture.

This role will lead technical architecture, define long-term platform strategy, influence technology roadmaps, and drive cross-functional initiatives.

Key Responsibilities

• Lead architecture and technical direction for:

  • Enterprise GenAI Platforms

  • Agentic AI Platforms

  • Model Serving Infrastructure

  • Agent Runtime Platforms

  • Prompt & Evaluation Frameworks

  • AI Governance & Guardrails

  • AI Observability & AI Operations

• Design and drive multi-cloud AI platform architecture across:

  • OpenShift AI / RHOAI

  • Google Cloud Platform Vertex AI

  • Azure AI Foundry

  • AWS Bedrock

  • Gemini, Anthropic Claude, and OpenAI models

• Define platform strategies for:

  • Kubernetes/OpenShift

  • GPU infrastructure

  • NVIDIA SuperPOD

  • Capacity planning

  • Multi-region architectures

  • High availability

  • Disaster recovery

  • Active-active architectures

• Drive architecture for highly scalable, secure, resilient Tier-1 production platforms.

• Partner with engineering, infrastructure, data, security, and business teams to establish technical roadmaps and architectural standards.

Must-Have Skills

Candidates should have strong hands-on experience with:

• Kubernetes / OpenShift

• AI/ML Platforms

• MLOps / AI Ops

• Cloud Architecture

• Distributed Systems

• Generative AI / LLM Platforms

• RAG Architectures

• Agentic AI

• Model Serving

• API Platforms

• Data Platforms

• High Availability & Disaster Recovery

• Production-scale cloud-native platforms

Preferred Experience

• 10+ years of experience in software engineering, infrastructure, and/or architecture.

• 5+ years designing and implementing large-scale cloud-native platforms.

• Experience with OpenShift AI / RHOAI, Google Cloud Platform Vertex AI, Azure AI Foundry, AWS Bedrock, or similar AI platforms.

• Experience with GPU infrastructure and NVIDIA SuperPOD environments.

• Experience architecting multi-cloud and multi-region platforms.

• Experience with enterprise AI governance, security, observability, and guardrails.

What the Client Is Looking For

Hands-on technical depth is critical. Candidates should be able to clearly explain:

• AI/ML platforms they have personally designed or implemented.

• Kubernetes/OpenShift architecture and production deployments.

• MLOps/AI Ops implementation.

• Cloud architecture decisions and trade-offs.

• GenAI, RAG, agentic AI, or model-serving projects.

• Scalability, resiliency, HA, and DR strategies used in real production environments.

Location Preference: Bay Area preferred; Charlotte considered as a secondary location.