Solutions Architect (AI/ML and Analytics Engineering) || Remote || 15+ Exp

Solutions Architect AI and Analytics Engineering

Reports to: Director of AI and Analytics Engineering

100% REMOTE

About the Role

• We are seeking a highly skilled Solutions Architect to support the buildout and evolution of our AI and Analytics Engineering platform, with a strong emphasis on Databricks, Mosaic AI, and enterprise-scale data systems.
• In this role, you will contribute to the design and implementation of scalable, maintainable, and interoperable AI and analytics solutions that power advanced learning experiences and decision intelligence. Under the guidance of the Director of AI and Analytics Engineering, you will collaborate across technical and business domains to ensure solutions are strategically aligned, technically sound, and enterprise-ready.

Key Responsibilities

Architecture & AI Engineering Strategy

• Architect and implement enterprise-grade AI and analytics systems using the Databricks suite, including Delta Lake, Unity Catalog, MLflow, and Mosaic AI for generative use cases.
• Evaluate and recommend the most appropriate AI/ML tools and frameworks for given problems, balancing scalability, integration, and maintenance considerations.
• Develop and maintain modular, interoperable ML and data pipelines, ensuring consistency, traceability, and ease of deployment across projects.
• Define and advocate for best practices in architectural design, data pipeline structuring, and production-readiness.

Cross-Functional Collaboration

• Under the direction of the Director, work with BI and analytics stakeholders to identify opportunities to evolve traditional reporting solutions into predictive and prescriptive analytics applications.
• Partner with their counterparts in internal teams including Infrastructure, InfoSec, and Applications Engineering to align on security, governance, deployment, and performance standards.
• Support the translation of high-level business objectives into detailed technical designs and guide their implementation across teams.

Delivery & Operationalization

• Build and optimize CI/CD-enabled data and ML workflows, with appropriate monitoring, testing, and automation.
• Ensure pipelines and models are reusable, scalable, and integrated with existing architecture and tooling.
• Document architectural decisions and implementation patterns to ensure continuity, supportability, and transparency across the organization.

Minimum Qualifications

• 6+ years of hands-on experience in data engineering, ML architecture, or AI platform development, ideally within an enterprise environment.
• Advanced experience with Databricks tools, including Delta Live Tables, MLflow, Unity Catalog, and Mosaic AI.
• Working experience with Analytics as well as low latency data, and architectural design constraints and considerations around each.
• Proficiency in Python, SQL, and Spark, with strong understanding of cloud-native data processing.
• Experience with CI/CD for data and ML workflows, using tools such as GitHub Actions, Azure DevOps, or Databricks-native integrations.
• Demonstrated ability to evaluate, select, and implement AI/ML tools for varied business needs.
• Strong understanding of enterprise systems architecture, security standards, and infrastructure interoperability.

Preferred Qualifications

• Experience deploying and orchestrating Generative AI systems or LLM pipelines, ideally using Mosaic AI or similar platforms.
• Familiarity with data observability and governance frameworks.
• Excellent communication and documentation skills, with the ability to clearly articulate tradeoffs and architectural recommendations.