Head of Data & AI Platform

Baker Tilly•San Diego, CA

4d•$250,000 - $400,000

About The Position

Baker Tilly is seeking a Head of Data & AI Platform to serve as the firm’s principal Data Architect for AI products and lead the team responsible for the data and intelligence foundation powering its AI product portfolio. The role owns the data layer end to end—including data architecture, modeling, engineering, and data science—as well as the intelligence capabilities of Compass, the BT Intelligence Platform: ontology, knowledge graph, judgment layer, product data estate, and supporting pipelines. This leader will define how data and practitioner knowledge are structured, connected, and transformed into reusable intelligence for AI products. They will establish a learning loop that uses production signals, practitioner feedback, outcomes, and traces to improve models, graphs, and retrieval quality. The role is a hands-on, player-coach position: personally shaping data architecture while building and leading a senior team across the U.S. and India. The Head will establish standards and roadmaps for data, knowledge-graph, machine-learning, and data science capabilities, and lead the transition of architecture and expertise from external partners to Baker Tilly teams. The position partners with Product Management, Architecture, Agent Engineering, Platform & Production Engineering, the enterprise data organization, subject matter experts, and engineering teams in India to ensure AI products have a scalable, high-quality, well-governed intelligence foundation.

Requirements

Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
15 years of experience across data architecture, data engineering, and data platforms, including technical leadership of senior engineering teams.
Demonstrated experience designing and delivering knowledge systems embedded within products, such as ontologies, knowledge graphs, semantic layers, or similar capabilities that directly support applications.
Deep expertise in knowledge representation, including ontologies, knowledge graphs, GraphRAG, and judgment or decision modeling.
Strong experience with data architecture and modeling, including enterprise and product data models, identity resolution, and data contracts.
Strong modern lakehouse experience using Databricks or equivalent technologies, including Delta Lake, medallion architecture, and structured and unstructured data pipelines at scale.
Experience designing and operating streaming and batch data pipelines and unstructured-document processing capabilities.
Deep understanding of retrieval architectures, including embeddings, vector search, hybrid graph and vector retrieval, and reranking approaches.
Experience building retrieval systems whose quality is measured, evaluated, and continuously improved.
Experience leading or closely partnering with data science and machine-learning teams to establish production learning loops.
Knowledge of applied data science practices for feedback capture, evaluation-driven improvement, and drift detection and management.
Experience with corpus engineering, including document extraction, ground-truth development, and synthetic data generation.
Demonstrated ability to design scalable data and intelligence architectures while remaining hands-on with complex technical challenges.
Experience leading distributed engineering teams and collaborating effectively across U.S.- and India-based organizations.
Experience transitioning architecture, engineering capabilities, or technical ownership from external partners to internal teams.
Strong ability to collaborate across Product, Architecture, Engineering, Data, and business subject matter experts to translate product and business needs into scalable technical solutions.
Demonstrated ability to use AI and agentic development tools as a force multiplier in day-to-day technical and leadership work.
Ability to operate effectively as a player-coach, balancing hands-on architecture and technical problem-solving with team leadership, talent development, and strategic direction.

Nice To Haves

Advanced degree.

Responsibilities

Own the Baker Tilly Intelligence Layer, including strategy, architecture, and roadmap for the ontology, knowledge graph, and judgment graph.
Design and build ontology, knowledge-graph, and judgment-graph capabilities with engineering teams across the U.S. and India.
Define how practitioner decisions, corrections, outcomes, and system traces are captured, curated, approved, and transformed into reusable intelligence.
Establish retrieval semantics across graph- and vector-based approaches, measuring retrieval and grounding quality through evaluation.
Own the data layer end to end, including data architecture, data modeling, product data models, the product data plane, extraction and integration pipelines, and data quality.
Establish and maintain medallion architecture standards, data contracts, identity-resolution approaches, and data-quality practices for the product data estate.
Build and maintain scalable structured and unstructured data pipelines for AI products and intelligence capabilities.
Partner with the enterprise data organization to consume enterprise data through established data contracts, identity standards, client-identity keys, and systems-of-record boundaries.
Own data science capabilities and establish the learning loop that uses production signals, practitioner feedback, outcomes, and traces to improve models, graphs, and retrieval.
Lead corpus engineering programs, including document extraction, ground-truth development, and synthetic data generation.
Establish approaches for measuring and improving retrieval quality, model performance, and drift through evaluation-driven practices.
Build and lead data, knowledge-graph, machine-learning, and data science teams across the U.S. and India.
Hire, mentor, and develop senior data engineers, knowledge-graph engineers, machine-learning engineers, and data scientists, while establishing a high technical bar.
Operate a paired-team model with the India engineering organization, setting standards and roadmaps while enabling strong build and operational ownership in India.
Lead the transition of data and intelligence architecture capabilities from expert partners to Baker Tilly through a structured shadow, pair, lead, and own model.
Translate partner-developed architecture into Baker Tilly-owned roadmaps, standards, patterns, runbooks, and internal expertise.
Partner with the Principal Product Manager for Compass / the Intelligence Platform on product roadmap, priorities, scope, and data requirements.
Partner with the Chief Architect to co-design semantic architecture and align the intelligence, agentic, and platform layers.
Collaborate with the Head of Agent Engineering to ensure Compass workflows and agentic experiences are grounded in high-quality data and retrieval capabilities.
Partner with Platform & Production Engineering on Intelligence Layer infrastructure, including vector and retrieval infrastructure, runtime environments, and production telemetry.
Collaborate with subject matter experts to ensure the Intelligence Layer accurately captures and represents practitioner knowledge and judgment.
Engage in special projects and perform other duties as assigned.