AI/ML Solutions Architect (GenAI & RAG)

Job Title: AI/ML Solutions Architect (GenAI & RAG)

Location: Grand Rapids Michigan 49544

Experience: 13+ Years

Duration: 18 Months Contract

Must Have: AI Code Generation (Copilot Cursoe Claude Code)

Overview / Summary

We are seeking an Experienced AI/ML Solutions Architect with 13+ years of software engineering and/or Data science experience, including 4+ years in AI/ML architecture roles. The role is responsible for defining AI/ML architecture strategy, designing end-to-end AI solutions, and leading architecture initiatives across Generative AI, LLMs, machine learning, and data platforms.

Key Responsibilities

• Define and drive the AI/ML architecture strategy across the organization.
• Design end-to-end AI solutions.
• Lead architecture for Generative AI, LLMs, and traditional machine learning models.
• Design scalable data pipelines and real-time/streaming architectures.
• Establish MLOps practices for model versioning, deployment, and monitoring.
• Collaborate with AI and Data teams to define and promote best practices in AI system design.
• Evaluate emerging AI technologies and define adoption strategies

Required Qualifications

• 10+ years of experience in software engineering and/or data science.
• 3 5+ years of experience in AI/ML architecture roles.
• Strong experience in AI/ML architecture and system design.
• Strong experience with RAG (Retrieval-Augmented Generation).
• Expertise in machine learning, deep learning, and NLP.
• Hands-on experience with LLMs and Generative AI (GPT, Llama, etc.).
• Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with cloud platforms including AWS, Azure, and Google Cloud Platform AI services.
• Strong knowledge of data engineering, including ETL pipelines, data lakes, and streaming architectures.
• Experience with MLOps tools such as MLflow, Kubeflow, SageMaker, and Vertex AI.
• Understanding of APIs, microservices, and distributed systems.
• Knowledge of vector databases.
• Experience with DevOps/CI-CD pipelines for machine learning.
• Exposure to AI governance and compliance.