Engineering Staff

Engineering Staff Mechanical / Aerospace
· Software
· Industrial Applications
· Data / AI

Location:
Seoul Type: Full-time F4GE is building an AI-native manufacturing infrastructre for defense and advanced hardware. We work across engineering workflows, factory operations, manufacturing data, and applied AI. We are hiring engineers across mechanical and aerospace engineering, software, industrial applications, and data/AI. We are looking for people who can take ownership of hard technical problems, work across disciplines, and build systems that hold up in real production environments. This is not a role for someone who only wants to work inside a narrow

job description
. Mechanical / Aerospace You may work on:
- Design for manufacturing and assembly
- Manufacturability and process engineering
- Production planning and engineering workflows
- Cost, cycle-time, and process analysis
- Manufacturing methods across machining, fabrication, composites, assembly, and other processes
- Technical evaluation of parts, assemblies, and production requirements
- Working with software and data teams to translate manufacturing knowledge into products and systems We are looking for engineers who understand that manufacturing is not just about designing a part that works. It also has to be produced reliably, repeatedly, and at the right cost. Software You may work on:
- Software used across engineering and factory environments
- Production and operational workflows
- Industrial and machine integrations
- Internal engineering tools
- Factory-floor applications
- Systems for quality, traceability, planning, and execution
- Infrastructure that connects different parts of the manufacturing process The software we build has to work outside a controlled software environment. You will need to understand how people, machines, and production systems actually operate. Industrial Applications / Forward Deployment Some of our most important engineering work happens directly with manufacturers. You may work on:
- Deploying F4GE systems in production environments
- Understanding how factories and production lines operate
- Connecting equipment and existing systems
- Working directly with operators and manufacturing engineers
- Troubleshooting technical and operational issues
- Translating real manufacturing problems into engineering requirements
- Building solutions when existing tools are not enough This role sits between product, engineering, and the factory floor. We are looking for people who are comfortable getting close to the problem rather than solving everything from a desk. Data / AI You may work on:
- Applied AI for manufacturing and engineering
- Manufacturing data infrastructure
- Engineering decision-support tools
- Production intelligence
- Computer vision and quality applications
- Automation of engineering and operational workflows
- Systems that help structure and use manufacturing information We care about AI where it improves how things are engineered, produced, inspected, or operated. Not AI for its own sake. What we’re looking for We care more about how you think and build than the exact title on your resume. You should be someone who:
- Learns technical domains quickly
- Thinks clearly from first principles
- Takes ownership of outcomes
- Can work through problems without a detailed playbook
- Is comfortable moving across software, hardware, data, and operations
- Builds, tests, and iterates quickly
- Pays attention to details
- Can communicate with engineers, operators, customers, and suppliers
- Wants to understand how manufacturing actually works
- Cares whether what you build works in the real world You may come from aerospace, automotive, robotics, manufacturing, software, industrial automation, data, AI, or another technical field. We care much more about what you can do than where you worked before. The role F4GE is still early. That means engineers here will have significant ownership over what gets built and how it gets built. You may join through one discipline and end up working across several. The people who solve the hardest problems early will have the opportunity to become technical leaders as the company grows. Compensation and equity will reflect the level of technical ability, ownership, and problem complexity expected from the role.