Sr. AI Technology Architect

Wise Skulls llc
Irving, United States of America
10 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Irving, United States of America

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Computer Vision
Azure
Information Engineering
Distributed Systems
Python
Machine Learning
AI Infrastructure
O-RAN
Google Cloud Platform
Large Language Models
IT Architecture
Generative AI
Containerization
AI Platforms
Kubernetes
Virtual Agents
Databricks
Microservices

Job description

  • Define and govern enterprise AI architecture including LLMs, RAG, Agentic AI, and Edge AI systems.
  • Establish reference architectures for cloud-native AI, GPU-based inferencing, and distributed workloads.
  • Architect and deploy LLM-powered solutions using RAG, embeddings, vector databases, and orchestration frameworks.
  • Design Agentic AI workflows leveraging tools such as LangChain, LangGraph, Azure AI, and Databricks.
  • Lead AI infrastructure strategy including GPU optimization and high-performance compute environments.
  • Build and scale AI platforms across AWS, Azure, and Google Cloud Platform ecosystems.
  • Lead development of advanced AI/ML models across NLP, computer vision, graph ML, and forecasting domains.
  • Architect Edge AI solutions for low-latency, distributed decision-making systems.
  • Establish governance for responsible AI, security, and compliance.
  • Mentor teams and drive innovation and capability development.

Requirements

  • 15+ years of experience in AI/ML, Data Science, or Technology Architecture.

  • Strong expertise in Generative AI, LLMs, RAG, and Agentic AI systems.

  • Proficient in Python, APIs, microservices, and data engineering frameworks.

  • Experience with cloud platforms (AWS, Azure, Google Cloud Platform) and containerization technologies.

  • Deep understanding of AI infrastructure including GPU optimization and benchmarking.

  • Proven ability to lead large-scale transformation programs. Preferred Qualifications & Experience

  • Experience in banking, telecom, healthcare, energy, or supply chain domains.

  • Exposure to Edge AI, O-RAN architectures, and distributed systems.

  • Advanced degree (PhD/Master's) in AI, Data Science, or related field.

  • Experience in Enterprise adoption of AI platforms and architecture standards.

  • Experience in Scalable deployment of AI solutions delivering measurable outcomes.

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