Why This Role

Most manufacturing companies end up with disconnected software: one system for engineering, one for manufacturing, one for quality, one for procurement, one forlogistics, and a large amount of human effort stitching the gaps together.

Aalo cannot scale that way. We are trying to compress the path from customer need todeployedAalo Pod, and that requires software and AI systems that connect engineering intent, supply chain, factory execution, quality evidence, delivery documentation, and operational feedback.

In this role, you will build the factory software layer that helps make that possible. The near-term work includes practical systems like machine shop interfaces, manufacturing workflows, integrations, inspection capture, and as-built traceability. The long-term work is larger: helping Aalo build an internal enterprise software system that lets manufacturing improve continuously as the company scales.

If successful, this role gives Manufacturing dedicated software capacity while keeping the architecture integrated with the rest ofAalo’sAI and internal software platform. It reduces manual handoffs, improves traceability, makes factory work easier to execute, and creates the data foundation for better engineering and manufacturing decisions over time.

You will be helping build that system from the inside.

About the role

We’rehiring an AI Solutions Engineer - Manufacturing to build the internal software systems that help Aalo manufacture reactors faster, safer, and with better traceability.

At Aalo, AI and software are becoming part of the operating system of the company. This role focuses on manufacturing: the factory workflows, integrations, interfaces, data capture, and AI-enabled tools that connect engineering intent to real production work on the floor.

This role reports intoAalo’sAI and internal software team for technical management, architecture, and platform consistency, while being embedded with and accountable to Manufacturing. The purpose of that structure is deliberate: manufacturing needs dedicated software capacity, and the resulting systems need to integrate cleanly with the broader enterprise architecture rather than becoming another isolated tool.

You will work closely with manufacturing engineering, machinists, quality, supply chain,logistics, engineering, and the broader AI team to turn real factory workflows into production software.Your job is to understand how work actually happens, build systems that operators trust, and make sure manufacturing software is not an afterthought.

This is a forward-deployed software and systems engineering role with strong manufacturing workflow, integration, productization, and AI-native development responsibilities.

Examples of the systems and workflows this role may touch include:

• Custom factory interfaces on top of ION or successor manufacturing systems

• Machine shop workflows for job queues, work-center filtering, material verification, inspection capture, and operator signoffs

• TeamCenter, CAD, drawing, model, revision, and manufacturing procedure integrations

• As-built traceability across parts, serial numbers, materials, inspection records, nonconformances, and delivery data packages

• AI-assisted manufacturing procedures, work instructions, inspection plans, and approval workflows

• Quality, receiving, inventory, kitting, supplier, and material flow systems

• Production-floor dashboards for open jobs, bottlenecks, work centers, and execution status

• Automated data capture that feeds engineering feedback loops, design optimization, digital twins, and future fleet manufacturing improvements

• Integrations across manufacturing, engineering, procurement, quality,logistics, testing, maintenance, and customer delivery workflows

• Long-term evolution from vendor-centric factory tooling toward Aalo-owned internal enterprise software

Common technology categories and engineering patterns in the stack include:

• Backend application development and scripting

• Internal web applications and workflow interfaces

• Relational and document-oriented databases

• APIs, integration services, and service-oriented backend systems

• Enterprise system integrations including manufacturing, PLM, document, procurement, and quality systems

• AI models, coding agents, agent harnesses, tool orchestration, and workflow automation

• Browser automation, data pipelines, background jobs, and operational glue across internal systems

• Containers, CI/CD, infrastructure as code, and internal deployment patterns

• Shared platform services for observability, evaluation, identity, secure model access, and auditability

• Cloud platforms, secure storage, enterprise authentication, secrets management, and permission boundaries

What you'll do

• Spend time with manufacturing teams on the floor, in the trailer, and in thesystemsthey 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 tooperatein 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

Required Qualifications

Strong engineering fundamentals

• You can design systems with clear data models, APIs, service boundaries, integration patterns, and permission models

• You write clear, maintainable code and can judge whether generated code is correct, secure, scalable, and maintainable