What are the responsibilities and job description for the AI Solution Architect for Cincinnati OH position at Amaze Systems Inc?
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:
Salary : $70 - $75