What are the responsibilities and job description for the Senior AI Architect position at TechVirtue LLC?
Job Title: Sr. AI Technology Architect
Location: Dallas, TX
Duration: Long Term Contract
Role Overview:
We are looking for a visionary AI Senior Technology Architect to lead enterprise-scale AI transformation initiatives. The ideal candidate will have deep expertise in Generative AI, Agentic AI, AI infrastructure, and cloud-native architectures, with a strong focus on delivering scalable, high-performance AI solutions that drive business value.
Key Responsibilities:
- 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 using tools such as LangChain, LangGraph, Azure AI, and Databricks.
- Lead AI infrastructure strategy, including GPU optimization and high-performance computing environments.
- Build and scale AI platforms across AWS, Azure, and Google Cloud Platform.
- Lead the development of advanced AI/ML models across NLP, Computer Vision, Graph ML, and Forecasting.
- Architect Edge AI solutions for low-latency, distributed decision-making.
- Establish governance for responsible AI, security, and compliance.
- Mentor engineering teams and drive innovation and capability development.
Required Qualifications:
- 15 years of experience in AI/ML, Data Science, or Technology Architecture.
- Strong expertise in Generative AI, LLMs, RAG, and Agentic AI.
- Proficiency 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 AI 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 a related field.
- Experience in enterprise adoption of AI platforms and architecture standards.
- Proven experience in scalable deployment of AI solutions delivering measurable business outcomes.