Manufacturing Systems Architect

CHAOS Industries•El Segundo, CA

7d•$150,000 - $220,000•Onsite

About The Position

As CHAOS Industries scales production of advanced defense systems, the systems and data infrastructure that support manufacturing become mission-critical. We are seeking a Manufacturing Systems Architect to own the architecture, integration, and evolution of the systems that power manufacturing operations across the company. Working closely with Manufacturing, Quality, Supply Chain, Engineering, Program Management, and Information Technology, you will lead the design and implementation of the manufacturing systems ecosystem—from operational databases and reporting infrastructure to ERP, MES, PLM, quality systems, and analytics platforms. You will establish the technical foundation that enables accurate decision-making, scalable production, and end-to-end traceability across the factory. This is a builder’s role: you will define how manufacturing data is captured, structured, integrated, governed, and consumed across the organization while creating scalable systems capable of supporting significant production growth.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Industrial Engineering, Engineering, Data Analytics, or a related technical discipline and 8+ years of relevant experience; or a Master’s degree and 6+ years; or, in lieu of a degree, 12+ years of directly related experience.
Hands-on experience designing and building manufacturing or operational data systems—data models, pipelines, and integrations—that you personally architected and shipped.
Deep, current expertise in SQL, relational (and ideally time-series) data modeling, database performance, and building data pipelines and reporting environments from scratch.
Stack-agnostic builder: deep enough in data and systems fundamentals to design on whatever platform fits the problem, and to migrate the architecture forward as the toolset evolves—not anchored to a single vendor or product.
Strong understanding of data governance, master data management, systems integration, and traceability principles.
Ability to translate operational requirements into scalable technical solutions.
Excellent communication and stakeholder-management skills.
U.S. citizenship is required: this role accesses export-controlled information and requires a U.S. Department of Defense (DoD) Secret security clearance—current, or the ability to obtain and maintain one.

Nice To Haves

Experience in aerospace, defense, manufacturing, or national-security environments.
Experience across the categories of systems we operate—MES/MOM, ERP, and modern data/ontology platforms. (Our current stack includes First Resonance ION, NetSuite, and Palantir Foundry; familiarity is a plus, not a requirement.)
Experience building manufacturing data warehouses, ontologies, or operational analytics environments that scaled with production.
Experience supporting digital manufacturing, Industry 4.0, factory automation, or manufacturing transformation initiatives.
Experience integrating manufacturing, quality, supply chain, and enterprise systems into a unified operational data environment.
Active U.S. Department of Defense Secret or Top Secret security clearance.

Responsibilities

Design and build the data models, schemas, and ontologies—and the pipelines and integrations—that power manufacturing execution, quality, supply chain, inventory, and production planning, independent of any single platform.
Make manufacturing data trustworthy and traceable end-to-end—from shop-floor capture through reporting—with the data integrity and lot/serial traceability defense production demands.
Integrate the manufacturing systems ecosystem—MES, ERP, PLM, quality, warehouse, and data platforms—into a coherent, queryable source of truth, and evolve that architecture as systems are added or replaced.
Build the reporting and analytics backbone that turns operational data into a single operating picture: throughput, quality, labor, capacity, inventory, and on-time delivery.
Own the technical vision and roadmap for manufacturing systems—defining how the data and systems layer scales to support significant production growth and future automation.
Lead root-cause investigations into systems, data-quality, and reporting issues, and build the fixes that keep them closed.