AI/ML Architect

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Summary:

In this role, you will serve as an AI/ML Architect leading architectural vision, design, and enablement of our AI and ML platforms. Position will play a central role in designing scalable, secure, and high-performance machine learning infrastructure that supports the full lifecycle of AI applications across our organization. Position brings deep hands-on experience in enterprise ML architecture, strong knowledge of Databricks and Spark, and ability to translate complex AI requirements into robust, governed platforms. Will work closely with engineering, data science, cloud infrastructure, and compliance teams to define and implement the blueprint for AI success.

Responsibilities:

• Design, document, and own end-to-end AI/ML system architectures-from data ingestion and feature pipelines to model deployment, monitoring, and governance.
• Define patterns and reference architectures for scalable ML workflows, including real-time and batch inference, feature stores, model registries, and CI/CD for ML.
• Establish technical standards and reusable frameworks that promote modularity, compliance, and high-availability.
• Architect and optimize cloud-based ML platforms leveraging Databricks, Delta Lake, and MLflow for large-scale experimentation, training, and model management.
• Guide the implementation of feature engineering pipelines using PySpark and SQL within Databricks.
• Enable shared environments for collaborative data science, model experimentation, and reproducible ML workflows.
• Partner with Security and Compliance teams to ensure architectures meet HIPAA, SOC 2, and internal risk and governance requirements.
• Implement best practices for data lineage, model versioning, and access control within ML pipelines.
• Ensure auditability, traceability, and observability are embedded in architectural patterns.
• Serve as a trusted advisor to senior engineering and data science leaders-translating AI use cases into scalable architectural strategies.
• Guide integration of AI components with enterprise data lakes, business intelligence tools, APIs, and decision systems.
• Influence build vs. buy decisions for AI tools, frameworks, and cloud-native services.

Qualifications:

• Relevant degree preferred.
• 7 or more years relevant experience.
• 3 or more years of experience designing and supporting Databricks environments for ML workloads, including Lakehouse and ML flow components.
• Strong proficiency with distributed computing frameworks (e.g., Spark, Ray, Dask) and cloud-native data services (Azure Data Lake, AWS S3, etc.).
• Deep understanding of model lifecycle management, reproducibility, and automation in production-grade ML systems.
• Strong coding skills in Python and SQL; comfort with Terraform, YAML, and CI/CD for infrastructure.
• Excellent communication and system documentation skills.
• Experience integrating ML architectures in regulated industries (healthcare, finance, government) preferred.
• Familiarity with identity management, RBAC, secrets management, and secure data movement in cloud environments preferred.
• Knowledge of modern MLOps tooling (KubeFlow, Argo Workflows, Airflow, BentoML, etc.) preferred.
• Exposure to real-time ML use cases (streaming inference, edge AI, or embedded AI systems).

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Estimated Hiring Range:

This position is also incentive eligible.

Vizient has a comprehensive benefits plan! Please view our benefits here:

http://www.vizientinc.com/about-us/careers

Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities

The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.