About the Company

Neon is building the next generation of aerospace systems as an AI-native, digitally integrated Tier-1 supplier. Our mission is to deliver aerospace hardware with speed, rigor, and first-pass quality through model-based engineering, a unified digital thread, and advanced manufacturing.

About the Role

We’re looking for a Digital Engineering Platform Architect to design and own Neon's data, integration, and AI/ML platform architecture. This is a hands-on role focused on building the digital backbone that connects our engineering, manufacturing, and enterprise systems.

Responsibilities

Integration & Digital Thread

Architect Neon's integration backbone across PLM, ALM, MBSE, ERP, and manufacturing systems.
Define interoperability frameworks (APIs, OSLC, middleware, event-driven systems).
Ensure full traceability across the engineering lifecycle.

Data Infrastructure

Design and deploy Neon's enterprise data lakehouse.
Build ingestion pipelines, transformation frameworks, governance, and lineage.
Ensure data is accurate, accessible, and high-quality.

AI/ML Enablement

Establish infrastructure for AI/ML workloads: data pipelines, vector databases, and model-serving frameworks.
Enable LLM integrations, predictive analytics, and model-based certification.
Partner with engineering to identify and deliver high-impact AI use cases.

Governance & Standards

Define standards for data management, integrations, and API practices.
Work with IT on infosec, compliance, and system hardening.
Create guidelines and playbooks for future engineers and data teams.

Leadership

Serve as Neon's SME for data architecture, integrations, and AI enablement.
Mentor engineers and influence cross-functional technical decisions.
Collaborate closely with IT, Systems Engineering, and Configuration Management.

What you'll Bring:

Bachelor’s or Master’s in Computer Science, Data Engineering, Systems Engineering, or related field; equivalent professional experience may be considered in lieu of a degree.
Minimum of 8 years of experience in data architecture, systems integration, or digital engineering platform development.
Proven expertise with data lakehouse technologies (Snowflake, Databricks, or equivalent).
Strong background in API design, middleware, and integration frameworks (OSLC, REST, GraphQL, event streaming).
Experience designing and deploying AI/ML infrastructure (vector DBs, model serving, data pipelines).
Hands-on proficiency with at least one modern programming language (Python, Rust, Java, or similar).
Deep understanding of digital engineering environments and how to connect them into a unified ecosystem.
Experience in aerospace, defense, or other highly regulated industries preferred
Familiarity with Siemens Teamcenter, Siemens Polarion, and Cameo System Modeler integrations.
Experience with MLOps tooling (MLflow, Kubeflow, or equivalent).
Cloud architecture experience (Azure, AWS, or GCP).
Knowledge of compliance requirements (ITAR, CMMC, ISO 27001, etc.)

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