About The Role: 

• We're looking for a Staff Software Engineer who wants real ownership in a fast-moving environment. 
• You'll help design, build, deploy, and operate the software that runs Urban Sky's manufacturing operation—a full-stack MRP system that tracks inventory, work orders, bills of materials, quality holds, and serialized parts from receiving through final integration. It's the operational backbone of how we actually build balloons. Because the company is growing quickly, the scope of the role will evolve over time, and you'll have meaningful influence over what we build next and how we build it. 
• You'll work shoulder-to-shoulder with the people using the software every day—manufacturing technicians, logistics coordinators, quality inspectors, and finance. There's no product manager between you and them. You'll learn how parts flow through the building, what makes a quarantine workflow painful at 3pm on a Friday, and how a missed traceability record turns into a compliance problem. Translating messy physical processes into clean software is most of the job. 
• The interfaces you build are for operators, not consumers. A shop-floor tech holding a tablet, scanning a barcode, working through a multi-step assembly procedure—that's your user. Touch targets, scanner integration, and drag-and-drop work instructions matter more than landing-page polish. 
• We operate in an aerospace-regulated environment (AS9100). Every mutation needs an audit trail. Serialized parts need end-to-end traceability. "Move fast and break things" doesn't apply to production data. We still move fast—but with the discipline that comes from knowing a corrupted record can ground a flight. 
• You don't need prior MRP or manufacturing experience. You do need to be excited—or at least not intimidated—by learning a complex business domain alongside the code. 
• If you enjoy small teams and solving ambiguous problems, this role is likely a great fit. 

What You'll Do 

• Our overall software team is roughly 7 people, and this team will be just 2 people, everyone works across the stack. That's not aspirational—it's required. A small team with real ownership only works if everyone can contribute quickly and adapt as the company and product evolve. 
• Senior engineers here build trust by shipping early and expanding their scope through demonstrated ownership. 

What we need you to do right away

• We expect senior engineers to become productive almost immediately. 
• In your first days and weeks, you will: 
  • Set up your environment and start committing code within your first day or two 
  • Learn existing systems by improving them, not by watching from the sidelines 
  • Fix bugs, tighten rough edges, and ship small enhancements to production 
  • Participate in deployments, debugging, and operational workflows 
  • Use AI tools from the start to understand the codebase and accelerate contributions 
  • Ask questions, propose improvements, and engage in technical decisions 
• You won't be waiting for a long ramp period. 
• You'll build context by doing real work that ships. 

What you will grow quickly into

• As you gain context, scope expands fast. 
• Within your first couple of months, you'll be expected to: 
  • Own meaningful areas of our stack across backend, frontend, and infrastructure 
  • Lead design and implementation of projects that may span quarters 
  • Make architectural decisions with an eye toward reliability, operability, and future change 
  • Work directly with operators and stakeholders—often non-engineers—to refine solutions 
  • Drive systems from concept → implementation → production → iteration → support 
  • Continuously simplify, improve, and evolve what you own 
  • Help the team move faster by raising technical quality and reducing friction 
• By this point, you're not just contributing—you're a primary owner. 
• There are no lanes to stay in and no handoffs to hide behind. 
• If something feels confusing to an operator, that's an engineering problem. 
• If a system is brittle, slow, or overbuilt, that's an engineering problem. 
• If a workflow on the shop floor doesn't match the software, that's an engineering problem. 
• If requirements change mid-stream, that's reality—and adapting thoughtfully is part of the job. 
• If AI-generated code is messy, that's also an engineering problem. 
• You'll own systems end-to-end, from design through production and long-term maintenance—even as those systems evolve. 

Our engineering principles 

• These principles guide how we build systems in a fast-moving, real-world environment. 
• Design for operations, not just implementation 
• Software doesn't stop at merge. We design systems that can be deployed, monitored, debugged, and safely operated under changing constraints. 
• Favor simple, adaptable systems 
• Clarity beats cleverness—especially when systems need to change quickly. 
• Own the full lifecycle 
• Engineers are responsible for their systems from design through production, operational support, and ongoing evolution. 
• Build reliability through feedback 
• Observability is a first-class concern. Logs, metrics, and traces help us understand how systems behave as usage and requirements change. 
• Use abstraction sparingly and intentionally 
• Abstractions should make change easier, not harder. If they obscure failures or slow iteration, they're the wrong choice. 
• Scale and evolve based on evidence 
• We increase complexity, performance, and scale in response to real operational needs—not speculative futures. 
• Leverage AI with engineering judgment 
• We use AI aggressively to increase velocity and explore solutions, while remaining fully accountable for correctness and maintainability. 
• Embrace iteration as the default 
• Progress comes from frequent adjustments and steady improvement, not rigid plans. 

AI-assisted development 

• AI isn't supplemental here. It's a core part of our SDLC. 
• We use Claude Code for feature implementation, run automated multi-agent code review on pull requests, and have AI-driven quality checks integrated into CI. A meaningful portion of production code is AI-written and human-shaped. The skill we care about isn't typing speed or autocomplete—it's the judgment to review, restructure, reject, or rewrite AI output until it's correct, readable, and operable. 
• We expect you to: 
  • Use AI tools daily for implementation, debugging, refactoring, and exploration 
  • Adapt quickly as tools, models, and workflows evolve 
  • Apply strong judgment to AI-generated code—you're accountable for what ships, not the model 
  • Use AI to build production systems, not just prototypes 
  • Treat AI as leverage, not a replacement for understanding 
• We care far more about how you use AI than which model you prefer. 

What we are looking for

• This is a senior role. We're optimizing for experience, judgment, and adaptability. 
• You likely have: 
  • 8+ years of professional software engineering experience 
  • Strong fundamentals in system design, data structures, and architecture 
  • Experience building and operating backend systems at scale 
  • Solid instincts for data modeling, schema design, and SQL 
  • Comfort with cloud infrastructure and modern DevOps practices 
  • Experience owning production systems in environments that evolve quickly 
  • Strong communication skills and the ability to collaborate as priorities shift 
• You probably enjoy: 
  • TypeScript and modern web development 
  • Designing clean APIs and well-structured monoliths 
  • Thinking carefully about data models, schemas, and migrations 
  • Infrastructure, reliability, and operational excellence 
  • Mentoring others and raising the bar for the team 
• Learning quickly and adjusting course as new information emerges

Technologies (not a checklist) 

• We currently work with technologies such as: 
  • TypeScript / JavaScript 
  • React, Vite, Mantine UI 
  • tRPC for API contracts 
  • PostgreSQL (raw SQL and migrations, not just an ORM) 
  • ClickHouse for analytics 
  • Playwright for end-to-end testing 
  • AWS, Terraform, Docker 
  • CI/CD pipelines 
• You don't need experience with every tool—but you should be comfortable learning new systems as the stack evolves. 

 Benefits 

• Salary $150,000 - $180,000 per year  
• Stock Options 
• Medical, Vision and Dental 
• Unlimited Vacation Days 
• Cell Phone Bill Stipend