AI Architect

VDart Inc; Austin (TX); On-site; USD 160,000 - 230,000; Full time

Job summary

VDart Inc. in Austin, TX is seeking an AI Architect with 16+ years of experience in AI and Enterprise Architecture to design and deliver enterprise-scale AI platforms on AWS, Azure, and Google Cloud. You will drive architecture strategy and oversee complex deployments across multiple Fortune 500 clients.

Lead multi-agent Agentic AI frameworks, memory management, tool chaining, and governance to ensure secure, scalable, production-grade solutions while guiding cross-functional teams and vendors.

Qualifications

• 16+ years of experience in AI and enterprise architecture.
• Led architecture and delivery for enterprise AI initiatives.
• Experience with AWS, Azure, and Google Cloud.
• Proven track record managing large global teams.
• Experience building scalable AI-powered platforms.

Responsibilities

• Define and govern AI architecture strategy.
• Lead cross-functional teams across clients and vendors.
• Deliver secure, production-grade AI solutions.
• Drive cost optimization and platform governance.
• Mentor engineers and enforce engineering standards.

Skills

AI Architecture

Enterprise Architecture

Leading Global Teams

Generative AI

Cloud & DevOps

Tools

AWS Bedrock

LangChain

Vector Databases

AWS Lambda

Step Functions

API Gateway

Vertex AI

SageMaker

PyTorch

TensorFlow

Terraform

Kubernetes

Job description

AI Architect

• Havin over 16+ years of experience in AI & Enterprise Architecture: Architected and delivered enterprise-scale AI-powered platforms including Agentic AI, RAG, LLM, and Master Data Management (MDM) solutions on AWS, Azure, and Google Cloud, enabling intelligent automation, knowledge retrieval, and enterprise decision-making.


• Generative AI & Agentic AI: Designed and deployed production Agentic AI frameworks using AWS Bedrock, LangChain, Vector Databases, Lambda, Step Functions, and API Gateway, implementing multi-agent orchestration, autonomous reasoning, memory management, tool chaining, and self-healing workflows that improved operational efficiency by 35%.


• Cloud, AI/ML & Data Engineering: Built scalable AI/ML pipelines using Vertex AI, SageMaker, PyTorch, TensorFlow, Ray, Airflow, BigQuery, PostgreSQL, Pub/Sub, Cloud Run, and Terraform, delivering intelligent data classification, predictive analytics, anomaly detection, and enterprise MLOps capabilities.


• Cloud Infrastructure, DevOps & Cost Optimization: Led cloud platform engineering using Terraform, Kubernetes, CI/CD, AWS, Azure, and GCP, driving infrastructure automation, governance, reusable microservice frameworks, and AI-driven cloud optimization initiatives that delivered significant cost savings.


• Technical Leadership & Enterprise Delivery: Led architecture, strategy, and execution for multiple enterprise AI initiatives, managing 27+ member global teams, collaborating with clients and vendors, establishing engineering standards, AI governance, reusable platform components, and delivering secure, scalable, production-grade solutions across Fortune 500 organizations.