Principal AI & Data Architect

Role overview

Lead the architecture of the data, knowledge, and AI foundation for software that supports manufacturing operations. You’ll design a flexible platform where each customer can model its own assets, processes, materials, people, constraints, and outcomes, and build the technical foundations used by product capabilities such as analytics, optimization, simulation, and AI agents.

Responsibilities

- Define an ontology framework and knowledge graph engine, including modeling primitives, authoring tools, and ways to evolve customer schemas safely. - Design how customer-defined models are stored, queried, and kept coherent across the platform at scale. - Set the architecture for foundation-model selection, retrieval, fine-tuning, evaluation, and integration into agent workflows. - Determine database and storage choices across graph, relational, vector, and time-series workloads. - Build data pipelines for ingestion, transformation, lineage, and governance of varied industrial sources, including control systems, business software exports, sensor streams, and documents. - Set technical direction, review key designs, mentor engineers, and work with company leadership on priorities.

Requirements

- Deep expertise in knowledge representation, including ontologies, knowledge graphs, semantic modeling, and meta-modeling. - Strong grounding in network theory and the ability to apply quantitative methods to practical problems. - Experience designing systems that support extensible customer-defined data models. - Relevant depth in AI and language-model architecture, knowledge retrieval, or agentic systems; the role encompasses model selection, evaluation, and integration. - A PhD, master’s degree, or equivalent industry experience in a quantitative discipline such as computer science, applied mathematics, systems engineering, physics, computational science, or operations research.

Nice to have

- Experience in manufacturing, industrial operations, or supply chains. - Background in optimization, simulation, multidisciplinary design optimization, or operations research. - Research or project experience with graph methods, language models, agent-based modeling, or applied AI for decision-making. - Experience taking early-stage systems from prototype to enterprise deployment. - Familiarity with industrial data standards such as ISA-95, OPC UA, B2MML, or MTConnect.

Benefits and work setup

- Full-time or part-time arrangements are available. - The role offers technical leadership over foundational architecture and close collaboration with company founders.