AI Architect | Charlotte, NC (Day-1 Onsite) | Contract (Only on W2)

Overview

On Site
Depends on Experience
Contract - W2
Contract - 12 Month(s)

Skills

Artificial Intelligence
Cloud Computing
Machine Learning (ML)
Microservices
Generative Artificial Intelligence (AI)
Google Cloud Platform
Python
Data Science
DevOps

Job Details

Job Overview:

We are seeking a highly skilled AI Architect to design and drive our Artificial Intelligence strategy and solutions. The ideal candidate will have deep expertise in Machine Learning (ML), Generative AI (GenAI), and Large Language Model (LLM) frameworks. This role involves architecting end-to-end AI systems, guiding development teams, and ensuring robust, ethical, and scalable AI implementations.

Key Responsibilities:

  • Define and execute the AI/ML architecture and roadmap, covering both traditional ML and Generative AI use cases.
  • Design end-to-end AI solutions encompassing data ingestion, feature engineering, model training, inference pipelines, and monitoring frameworks.
  • Lead the integration of LLMs and RAG (Retrieval-Augmented Generation) frameworks using tools such as LangChain, LangGraph, or similar.
  • Collaborate with cross-functional teams to translate business objectives into AI-driven solutions.
  • Evaluate and recommend AI/ML tools, cloud services, and frameworks best suited for each use case.
  • Ensure model governance, security, explainability, and adherence to ethical AI practices.
  • Partner with engineering teams to implement scalable and high-performance AI components.
  • Work closely with DevOps to establish CI/CD pipelines for AI, including model versioning, deployment, and A/B testing.
  • Stay updated on AI research, trends, and innovations, providing strategic recommendations for adoption.

Qualifications:

  • Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
  • Proven experience in AI/ML solution architecture and cloud-based deployments (AWS, Azure, or Google Cloud Platform).
  • Hands-on experience with LLMs, RAG, vector databases, and prompt engineering.
  • Strong programming skills in Python and familiarity with ML libraries such as TensorFlow, PyTorch, or Hugging Face.
  • Experience designing scalable microservice-based AI systems.
  • Excellent communication, collaboration, and problem-solving skills.

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