Job Description: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 that powers the firm's AI product portfolio. This role will own the data layer end to end, including data architecture, data modeling, data engineering, and data science, as well as the intelligence capabilities that make up Compass, the BT Intelligence Platform, including the ontology, knowledge graph, judgment layer, product data estate, and supporting pipelines.
The Head of Data & AI Platform will define how data and practitioner knowledge are structured, connected, and transformed into reusable intelligence for the firm's AI products. This leader will also establish the learning loop through which production signals, practitioner feedback, outcomes, and traces are used to continuously improve models, graphs, and retrieval quality.
This is a hands-on, player-coach role responsible for personally shaping the data architecture while building and leading a senior team across the U.S. and India. The role 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 Head of Data & AI Platform will partner closely with Product Management, Architecture, Agent Engineering, Platform & Production Engineering, the enterprise data organization, subject matter experts, and engineering teams in India to ensure the firm's AI products are built on a scalable, high-quality, and well-governed intelligence foundation.
Responsibilities- Own the Baker Tilly Intelligence Layer, including the strategy, architecture, and roadmap for the ontology, knowledge graph, and judgment graph that determine what the firm's AI products know and how practitioner judgment is captured and reused.
- Design and build ontology, knowledge-graph, and judgment-graph capabilities in partnership 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, with retrieval and grounding quality measured 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 pipelines for structured and unstructured data supporting the firm's 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 through which production signals, practitioner feedback, outcomes, and traces improve models, graphs, and retrieval.
- Lead corpus engineering programs, including document extraction, ground-truth development, and synthetic data generation, to support the Intelligence Layer.
- Establish approaches for measuring and improving retrieval quality, model performance, and drift through evaluation-driven practices.
- Build and lead the 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 across the organization.
- Operate a paired-team model with the India engineering organization, establishing standards and roadmaps across the broader team 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 the semantic architecture and ensure alignment across 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 the infrastructure supporting the Intelligence Layer, 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.
Qualifications- Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience; advanced degree preferred.
- 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, including 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 in which 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.
- No certifications or licenses required.
The pay range for this position is $250,000 to $400,000. This range represents a good-faith and reasonable estimate of the compensation the firm expects to pay for this position at the time of posting. Actual compensation will depend on a variety of relevant factors, including an applicant's skills, experience, qualifications, professional certifications, work arrangements, geographic location, and other business and organizational needs. It is not typical for an individual to be hired at or near the top of the range, and compensation decisions depend on the facts and circumstances of each case. Baker Tilly offers a compensation and benefits package to eligible employees.
