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