Senior AI/ML Data Model Architect

Sapience AI Corporation•Seattle, WA

11d•$204,000 - $216,000

About The Position

Sapience AI is hiring a Senior AI/ML Data Model Architect to own the data models, schemas, and representations that connect professional communities’ knowledge to AI models, the KO graph, and the COGENT architecture. The role sits at the intersection of data architecture and machine learning, defining how knowledge is modeled, how features and embeddings are represented, and how data flows from raw sources into systems for retrieval, reasoning, and model use. The architect is accountable for a coherent, trustworthy data foundation across communities and platform systems. This includes designing schemas and representations for models, retrieval, and graphs; establishing data lineage, provenance, consistency, quality, privacy, and governance by design; aligning teams around shared foundations; and evolving the architecture as the platform and its AI systems grow. The role partners with engineering teams that implement pipelines and graph systems, and is focused on production data architecture rather than analytics or open-ended research. The role uses AI to explore schema options, reason about representations, and accelerate work, while the architect remains responsible for judgment, interpretation, quality, and design decisions. Success means consistent models across systems, effective retrieval and reasoning, traceable data, structurally sound quality and correctness, protected sensitive knowledge, and a foundation that can scale without constant rework.

Requirements

Seven or more years of experience in data architecture, data modeling, or a closely related field.
Experience designing data models and representations for machine learning or AI systems.
Strong grounding in schema design, data modeling, and knowledge representation.
Experience with features, embeddings, and representations for models and retrieval.
Strong understanding of data lineage, quality, and governance.
Fluency across relational, graph, and vector data paradigms.
Ability to align multiple teams around a shared foundation.

Nice To Haves

Experience with knowledge graphs and neuro-symbolic systems.
Experience architecting data for retrieval-augmented and reasoning systems.
Experience with privacy, governance, and sensitive data by design.
Familiarity with CRM, AMS, or knowledge-platform data.
Experience carrying a data architecture through significant growth.
Experience with graph and vector data is strongly preferred.

Responsibilities

Design data models and schemas that represent community knowledge for AI, maintaining coherence across communities and systems while balancing flexibility with the structure needed for reasoning and trust.
Design knowledge representations for models, retrieval, and the KO graph, including the feature and embedding representations AI systems depend on.
Align representations so neural and symbolic systems can work together.
Architect data flows from raw sources to models, the graph, and reasoning systems.
Own data lineage and provenance so data can be traced and trusted, and make data flows observable and reliable.
Set standards for consistency and quality across the platform, preventing fragmentation and divergent models and making correctness a property of the design.
Design data models that protect sensitive community knowledge and support governance, privacy, and access controls.
Partner with knowledge graph, applied AI, infrastructure, and research teams on shared representations and resolve cross-team data questions.
Align teams around a common data foundation rather than local models.
Evolve data models as the platform, communities, and AI systems grow, designing for scale and change without constant rework.
Use AI to explore schema options and representations while retaining ownership of design judgment, coherence, quality, and trustworthiness.