AI Solution Architect

Amaze Systems Inc
Cincinnati, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Cincinnati, United States of America

Tech stack

Java
API
Artificial Intelligence
Data analysis
Automation of Tests
Azure
Cloud Engineering
Continuous Integration
Information Engineering
DevOps
Github
Machine Learning
Systems Development Life Cycle
Release Management
Azure
Google Cloud Platform
Delivery Pipeline
Large Language Models
Spring-boot
IT Architecture
Multi-Cloud
Kubernetes
Machine Learning Operations
Virtual Agents
Data Pipelines
Databricks
Microservices

Job description

  • 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.

Requirements

  • 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., * 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.

Apply for this position