Senior AI Architect, Semantic Layer – Algorithm

This is a fully remote position, open to applicants in United States.

📋 Description

• Define and enhance the technical architecture for Dynata's semantic layer, medallion architecture, and enterprise data models.

• Convert business concepts, governance standards, and domain definitions into scalable technical frameworks and enforceable architectures.

• Set standards for schema design, metadata management, interoperability, and semantic consistency across the platform.

• Ensure that analytical, operational, and AI use cases are backed by a unified architectural foundation.

• Design and manage data contract frameworks for dependable, reusable, and trustworthy data assets.

• Establish criteria for schema validation, versioning, lineage, quality controls, and the controlled evolution of enterprise datasets.

• Collaborate with governance stakeholders to implement policies through technical controls and platform capabilities.

• Advocate for consistency, traceability, and discoverability across enterprise data assets.

• Define architectural patterns for feature stores, model inputs and outputs, model lifecycle management, and algorithm interoperability.

• Set standards for integrating analytical models, machine learning solutions, and AI services with enterprise data assets.

• Create scalable frameworks for feature reuse, model governance, and algorithm deployment.

• Ensure that AI and machine learning capabilities utilize secure, governed, and reusable platform foundations.

• Collaborate with Product, Technology, Research & Data Science, and Data Platform teams.

• Translate intricate technical concepts into architectural decisions and implementation guidance.

• Lead architectural discussions by balancing business needs, governance requirements, technical feasibility, and long-term scalability.

• Act as a technical thought leader on semantic architecture, data governance, AI enablement, and enterprise platform design.

• Report to the VP, Research & Data Science.

⛳️ Requirements

• Over 7 years of experience in data architecture, platform architecture, AI/ML infrastructure, data engineering, or related fields.

• Proven track record in designing enterprise-scale semantic layers, data models, schema governance frameworks, or data contract architectures.

• Strong knowledge of modern lakehouse architectures, medallion design patterns, metadata management, and data governance principles.

• Demonstrated experience in architecting machine learning and AI platforms, including feature stores, model lifecycle management, lineage, and governance capabilities.

• Experience in establishing technical standards that facilitate analytics, machine learning, and AI-driven applications at scale.

• Solid understanding of schema management, metadata frameworks, versioning strategies, and interoperability patterns.

• Experience translating unclear business requirements and governance concepts into scalable technical architectures.

• Excellent communication and stakeholder management skills, with experience influencing technical leaders, architects, and executive stakeholders.

• Proven success in effectively navigating ambiguous environments and leading foundational platform and architecture initiatives.

• Familiarity with modern data and AI platforms such as Databricks, DataHub, Snowflake, feature stores, metadata platforms, or similar technologies.

• Preferred: Experience in implementing or governing enterprise semantic layers and business glossaries.

• Preferred: Knowledge of AI governance, model governance, and responsible AI frameworks.

• Preferred: Experience in designing architecture for graph analytics, forecasting, optimization, or decision-support systems.

• Preferred: Exposure to LLM-enabled platform capabilities such as metadata generation, semantic modeling, catalog enrichment, or governance automation.

🏝️ Benefits

• A discretionary incentive program may be included as part of the compensation package.

• Comprehensive medical and other benefits, depending on full-time employment status.

• An inclusive and accessible work environment.

• Accommodations available upon request for all aspects of the selection process.