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AI Solution Architect for Cincinnati OH

Job

Amaze Systems Inc

Cincinnati, OH (In Person)

Full-Time

Posted 5 days ago (Updated 2 days ago) • Actively hiring

Expires 7/7/2026

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Job Description

AI Solution Architect for
Cincinnati OH Key Responsibilities Brownfield Development:
Modernize legacy applications by embedding AI/ML capabilities while maintaining backward compatibility.
Cloud Architecture:
Design and deploy scalable AI solutions leveraging Azure Cognitive Services, Google Cloud Platform Vertex AI, and containerized microservices.
Java Tech Stack:
Architect AI modules within Java/Spring Boot applications, ensuring performance and maintainability.
Data Engineering:
Build and optimize data pipelines using Databricks for AI workloads, integrating structured and unstructured data sources.
CI/CD Automation:
Implement robust CI/CD pipelines using GitHub Actions and Harness to streamline AI model deployment and application releases.
Testing & Validation:
Establish automated testing frameworks for AI models, ensuring fairness, robustness, and compliance.
Cross-Team Collaboration:
Partner with sprint teams to align AI architecture with product roadmaps and delivery timelines.
Governance & Compliance:
Ensure adherence to ethical AI standards, data privacy regulations, and enterprise governance frameworks Experience with driving teams through AI/Agentic AI implementation across SDLC phases and AI-first coding. Experience with Agentic AI frameworks like LangChain/LangGraph, MS Agent Framework, CrewAI for custom agent development along with MCP. Proven experience working with business partners & product teams to ideate, conceptualize & scale AI solutions. Exposure tools like Claude Code, GHCP, MS Fabric, Anthropic, Gemini, and OpenAI LLM models. Required Skills & Experience Proven expertise in AI/ML architecture and cloud-native design. Hands-on experience with Azure AI services and Google Cloud AI/ML APIs. Strong proficiency in Java, Spring Boot, and microservices. Advanced knowledge of Databricks for data engineering and analytics. Experience with CI/CD pipelines using GitHub Actions and Harness. Familiarity with DevOps practices, container orchestration (Kubernetes), and automated testing. Understanding of AI governance frameworks and responsible AI practices. Preferred Qualifications Experience in multi-cloud deployments (Azure + Google Cloud Platform). Exposure to MLOps frameworks (Kubeflow, MLflow). Strong background in data engineering pipelines for AI workloads. Ability to mentor sprint teams in adopting AI-first practices. Rahul Sharma |
Team Lead Amaze Systems Inc E: