AI Solution Architect
Location-
Cincinnati OH
Salary- ***K/Y
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, GCP 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 + GCP).
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.
The pay range for this role is *** - **** per annum including any bonuses or variable pay. *** also offers benefits like medical, vision, dental, life, disability insurance and paid time off (including holidays, parental leave, and sick leave, as required by law). Ask our recruiters for more details on our Benefits package. The exact offer terms will depend on the skill level, educational qualifications, experience and location of the candidate.
*** is an Equal Employment Opportunity employer. We promote and support a diverse workforce at all levels of the company. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, age, national origin, or disability. All applicants will be evaluated solely on the basis of their ability, competence, and performance of the essential functions of their positions with or without reasonable accommodations. Reasonable accommodations also are available in the hiring process for applicants with disabilities. Candidates can request a reasonable accommodation by contacting the company ADA Coordinator at
***
.