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Pod Factory Jobs (NOW HIRING)

We are trying to compress the path from customer need to deployed Aalo Pod, and that requires software and AI systems that connect engineering intent, supply chain, factory execution, quality ...

... Factory for Terraform (AFT) and the private Terraform module library * Own runbook authorship, ownership, and execution; pair with the Monitoring pod within Foundations on the feedback loop from ...

Lead Data Engineer - NBA

Nashville, TN

$99K - $130K/yr

Key Responsibilities Pod delivery - Own end-to-end delivery for the data engineering pod, including ... Familiarity with Azure Data Factory, Azure Event Hubs, Azure Data Lake Storage, and broader Azure ...

Lead Data Engineer - NBA

Nashville, TN

$99K - $130K/yr

Key Responsibilities Pod delivery - Own end-to-end delivery for the data engineering pod, including ... Familiarity with Azure Data Factory, Azure Event Hubs, Azure Data Lake Storage, and broader Azure ...

Lead Data Engineer - NBA

Nashville, TN · On-site

$99K - $130K/yr

Key Responsibilities Pod delivery - Own end-to-end delivery for the data engineering pod, including ... Familiarity with Azure Data Factory, Azure Event Hubs, Azure Data Lake Storage, and broader Azure ...

... Factory for Terraform (AFT) and the private Terraform module library * Own runbook authorship, ownership, and execution; pair with the Monitoring pod within Foundations on the feedback loop from ...

... Factory for Terraform (AFT) and the private Terraform module library * Own runbook authorship, ownership, and execution; pair with the Monitoring pod within Foundations on the feedback loop from ...

Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Support pod-level delivery by producing reusable data assets and integration components that can be ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

Support pod-level delivery by producing reusable data assets and integration components that can be ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Automation Controls Leader

Oakland, CA · On-site

$88K - $147K/yr

Beyond the home site, this leader may support a regional pod of plants, providing technical ... Own factory-floor network design, performance, cybersecurity posture, and obsolescence planning

Data Engineer

Wilmington, DE · On-site

$111K - $133K/yr

Support pod-level delivery by producing reusable data assets and integration components that can be ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Data Engineer

Houston, TX · On-site

$109K - $131K/yr

Support pod-level delivery by producing reusable data assets and integration components that can be ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Support pod-level delivery by producing reusable data assets and integration components that can be ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

Support pod-level delivery by producing reusable data assets and integration components that can be ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Data Engineer

Boston, MA · On-site

$124K - $149K/yr

Support pod-level delivery by producing reusable data assets and integration components that can be ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

Support pod-level delivery by producing reusable data assets and integration components that can be ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Showing results 21-40

Pod Factory information

See salary details

$11K

$55.4K

$90K

How much do pod factory jobs pay per year?

As of Sep 2, 2026, the average yearly pay for pod factory in the United States is $55,409.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,000.00 and $61,000.00 per year, depending on experience, location, and employer.

What is a pod factory?

A Pod Factory typically refers to a company or facility specializing in the manufacturing and assembly of modular pods. These pods can serve various purposes, such as portable offices, living quarters, classrooms, or even specialized units for healthcare or hospitality. The factory uses prefabrication techniques to build these modules efficiently, allowing for quick deployment and installation on-site. Pod Factories often emphasize sustainability, cost-effectiveness, and customization to meet different client needs.

What are the typical responsibilities and challenges faced by employees working in a pod factory environment?

Employees in pod factory settings are typically tasked with operating machinery, assembling pods, conducting quality checks, and maintaining a clean and safe workspace. One common challenge is adhering to strict production quotas while ensuring product quality is not compromised. Teamwork is essential, as workers often rotate stations and collaborate to troubleshoot minor equipment issues. The work environment is usually fast-paced, and attention to detail is crucial to avoid production errors. Opportunities for advancement often depend on mastering different stations and demonstrating reliability and initiative.

What are the key skills and qualifications needed to thrive as a pod factory worker, and why are they important?

To thrive as a Pod Factory Worker, you generally need a high school diploma or equivalent, strong attention to detail, and basic mechanical aptitude. Familiarity with manufacturing equipment, assembly line systems, and safety certifications like OSHA are typically important. Reliability, teamwork, and adaptability are standout soft skills in this role. These skills ensure efficient production, product quality, and a safe working environment in fast-paced factory settings.
Infographic showing various Pod Factory job openings in the United States as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, 2% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $55,409 per year, or $26.6 per hour.

AI Solutions Engineer (Manufacturing)

MCJ

Austin, TX • On-site

$85 - $120/hr

Other

PTO

Posted 15 days ago


Job description

Aalo Atomics is pioneering a new era in clean energy with factory-fabricated microreactors designed to deliver affordable, scalable, and reliable nuclear power. Our mission is to make nuclear energy globally accessible, starting with the Aalo-1, a 10 MWe reactor leveraging cutting‑edge safety, modularity, and efficiency. Based in Austin, TX, we’re rapidly growing as we work to deploy the world’s first fleet of advanced microreactors. Join us and help revolutionize energy for a sustainable future.

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 for logistics, 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 to deployed Aalo 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 of Aalo’s AI 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’re hiring 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 into Aalo’s AI 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
  • 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 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
Required Qualifications
  • 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
  • You understand the difference between a useful prototype and a production system that real operators can rely on
  • You know how to keep workflow software simple without creating fragile architecture or disconnected data silos
Manufacturing and operations mindset
  • You are motivated by software that changes how physical work gets done, not just software that looks good in a demo
  • You are comfortable learning from machinists, manufacturing engineers, quality teams, inventory teams, and operators
  • You care about traceability, revision control, as‑built records, material flow, inspection evidence, and operational handoffs
  • You can work from messy reality: incomplete systems, manual workarounds, vendor constraints, edge cases, and urgent production needs
High output and follow‑through
  • You are comfortable taking incomplete requirements, rough workflows, or painful manual processes and turning them into working systems
  • You handle integrations, stakeholder feedback, production issues, and edge cases without losing momentum
  • You care about adoption and operational value, not just technical novelty
  • You can stay focused on factory software priorities while still integrating with the broader company‑wide AI and software platform
  • You already use AI coding agents or agentic development workflows as part of your daily engineering process
  • You have demonstrated interest in AI through real projects, experiments, evaluations, or sustained use of new models and tools
  • You can guide, evaluate, and refine AI‑generated code rather than relying on it blindly
  • You think in terms of leverage, fast feedback loops, evaluation, and compounding workflow improvements
  • You are comfortable being embedded with manufacturing while staying technically connected to the AI and internal software team
  • You communicate clearly with technical and non‑technical stakeholders and can bridge shop‑floor reality with software architecture
  • You are willing to sit with users, observe workflows, ask basic questions, and build trust through useful systems
  • You optimize for company outcomes, integrated systems, and long‑term maintainability rather than narrow ownership boundaries
Interest in where this is going
  • You are excited by the idea that manufacturing, engineering, supply chain, quality, and delivery can become a connected software‑driven system
  • You want to help build the internal enterprise software that Aalo uses to manufacture reactors at scale
  • You are comfortable working in a role that will evolve as AI tools, factory systems, and Aalo’s manufacturing model become more capable
Preferred Qualifications
  • 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
Requirements
  • 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
What We Offer
  • Paid Time Off
Additional Information

Aalo Atomics provides a collaborative and supportive work environment, opportunities for professional growth, intellectually challenging careers, and competitive compensation. Aalo Atomics is an equal opportunity employer and considers all employment decisions without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, veteran status, or any other characteristic protected by law.

Applicants must be U.S. Citizens or U.S. Persons in compliance with 10 CFR Part 810 and may not hold non‑compliant foreign citizenships.

Direct applicants only. No recruiters or staffing agencies, please.

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