AI Solutions Engineer (Manufacturing)

Aalo Atomics • Austin, TX

8d • Onsite

About The Position

This role focuses on building the internal software systems that help Aalo manufacture reactors faster, safer, and with better traceability. AI and software are becoming integral to Aalo's operations, and this position specifically targets manufacturing workflows, integrations, interfaces, data capture, and AI-enabled tools that bridge engineering intent with production work. The role reports to Aalo’s AI and internal software team for technical guidance and platform consistency, while being embedded with and accountable to the Manufacturing department. This structure ensures dedicated software capacity for manufacturing while maintaining integration with the broader enterprise architecture. The engineer will collaborate closely with manufacturing engineering, machinists, quality, supply chain, logistics, engineering, and the AI team to translate real factory workflows into production software, ensuring that manufacturing software is not an afterthought but a core component. This is a forward-deployed software and systems engineering role with responsibilities in manufacturing workflows, integration, productization, and AI-native development. The role may involve working with systems such as custom factory interfaces, machine shop workflows, integrations with PLM and CAD systems, as-built traceability, AI-assisted manufacturing procedures, quality and inventory systems, production-floor dashboards, and automated data capture for feedback loops. The technology stack includes backend development, internal web applications, databases, APIs, enterprise system integrations, AI models, containers, CI/CD, and cloud platforms.

Requirements

• Strong engineering fundamentals: ability to design systems with clear data models, APIs, service boundaries, integration patterns, and permission models.
• Ability to write clear, maintainable code and judge whether generated code is correct, secure, scalable, and maintainable.
• Understanding the difference between a useful prototype and a production system that real operators can rely on.
• Knowledge of how to keep workflow software simple without creating fragile architecture or disconnected data silos.
• Manufacturing and operations mindset: motivated by software that changes how physical work gets done.
• Comfortable learning from machinists, manufacturing engineers, quality teams, inventory teams, and operators.
• Care about traceability, revision control, as-built records, material flow, inspection evidence, and operational handoffs.
• Ability to work from messy reality: incomplete systems, manual workarounds, vendor constraints, edge cases, and urgent production needs.
• High output and follow-through: comfortable taking incomplete requirements, rough workflows, or painful manual processes and turning them into working systems.
• Ability to handle integrations, stakeholder feedback, production issues, and edge cases without losing momentum.
• Focus on adoption and operational value, not just technical novelty.
• Ability to stay focused on factory software priorities while still integrating with the broader company-wide AI and software platform.
• AI-native working style: already use AI coding agents or agentic development workflows as part of your daily engineering process.
• Demonstrated interest in AI through real projects, experiments, evaluations, or sustained use of new models and tools.
• Ability to guide, evaluate, and refine AI-generated code rather than relying on it blindly.
• Thinking in terms of leverage, fast feedback loops, evaluation, and compounding workflow improvements.
• Team-first mindset: comfortable being embedded with manufacturing while staying technically connected to the AI and internal software team.
• Clear communication with technical and non-technical stakeholders, bridging shop-floor reality with software architecture.
• Willingness to sit with users, observe workflows, ask basic questions, and build trust through useful systems.
• Optimizing for company outcomes, integrated systems, and long-term maintainability rather than narrow ownership boundaries.
• Interest in the idea that manufacturing, engineering, supply chain, quality, and delivery can become a connected software-driven system.
• Excited to help build the internal enterprise software that Aalo uses to manufacture reactors at scale.
• Comfortable working in a role that will evolve as AI tools, factory systems, and Aalo’s manufacturing model become more capable.
• Based in the United States.
• Willing to work on-site in Austin, TX.
• Willing to work closely with manufacturing teams in person, including time spent near the factory floor and production workflows.

Nice To Haves

• Experience in manufacturing, industrial systems, aerospace, energy, nuclear, hardware, logistics, or other physical-world domains.
• Experience with MES, ERP, PLM, QMS, inventory, work-order, or factory execution systems.
• Familiarity with ION, TeamCenter, CAD/CAM, machine shop workflows, inspection workflows, or as-built documentation.
• Experience working in regulated, high-reliability, audit-sensitive, or compliance-sensitive environments.
• Background in internal tools, integrations, workflow software, operational systems, or technical business processes.
• Experience building software used by non-software teams in production environments.

Responsibilities

• Spend time with manufacturing teams on the floor, in the trailer, and in the systems they use every day to understand real workflows before designing software around them.
• Build and iterate factory software from first prototype to production through integration, edge-case handling, testing, hardening, rollout, and adoption support.
• Create operator-friendly interfaces that simplify manufacturing work while preserving traceability, auditability, permissions, and source-of-truth data integrity.
• Integrate systems across ION or successor manufacturing platforms, TeamCenter, engineering documents, quality records, inventory, supplier data, and internal AI platform services.
• Build AI-enabled workflows that improve manufacturing procedures, inspection plans, material verification, job routing, as-built documentation, and operational decision-making.
• Review, debug, and refine AI-generated code and workflows to ensure they are useful, maintainable, secure, and safe to operate in manufacturing contexts.
• Capture production data in ways that support manufacturing execution today and engineering optimization, digital twins, and fleet-scale learning over time.
• Work closely with platform engineers to reuse shared AI infrastructure rather than building isolated one-off systems.
• Own meaningful factory software outcomes rather than acting only as a service desk for ad hoc manufacturing requests.
• Help define how Aalo builds in-house enterprise software for a manufacturing company whose systems must span engineering, supply chain, production, quality, logistics, testing, maintenance, and delivery.

Benefits

• Health, Dental, Vision Insurance
• Paid Time Off
• Corporate Gym Membership

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed