Software Engineer
Backend-focused, full-stack · 5+ years 
We are looking for a strong software engineer who can take a problem from a half-formed business idea to a running production system. This is not an operator role, and it is not a role for someone who only closes tickets. You will be handed problems that are vague or incomplete, and we expect you to figure out what is actually being asked, propose a design, make the calls, build it, ship it, and support it once it is live.Most of the work leans backend, with regular frontend work alongside it. AI is part of the picture too: you will be integrating models into real products, not running isolated experiments. We care far more about your engineering judgment than your prompt-writing, and we will dig into that judgment during the interviews.
What you'll do
• Take ambiguous or high-level requirements, clarify the real problem, and turn it into a clear technical proposal.
• Surface risks early, weigh the tradeoffs, pick a direction, and be ready to defend the decision later.
• Build and release the work yourself, then own it in production, including the bugs, incidents, and scaling problems that follow.
• Split your time roughly 60–70% backend and 30–40% frontend.
• Integrate AI into production systems, working through orchestration, high-throughput workloads, workload management, and the design of solutions that hold up at scale.
• Work directly with architects, senior engineers, and product and business stakeholders rather than waiting for fully specified tasks.
What we're looking for
More than five years of professional experience, with a real track record of shipping and supporting projects across more than one production environment. The fundamentals are the core of this role, so you should be comfortable being interviewed on:
• System design and architecture tradeoffs.
• Scalability, maintainability, and testing.
• Release strategy, debugging, and production support.
We are looking for someone who can work without heavy mentorship, onboard quickly, and think about the product rather than just the feature in front of them. You should use AI as a genuine productivity tool while staying skeptical of what it gives you, catching weak decisions, missing context, and gaps in generated output before they reach production.
Signals that stand out
• End-to-end ownership, from idea to production.
• Clear decision-making and the ability to explain why you chose one approach over another.
• Hands-on experience with releases, real incidents, and scalability concerns.
• Exposure to strong engineering standards across different teams and contexts.
What this role isn't
This is a hands-on engineering role. Experience centered mainly on cost optimization, SRE, or DevOps is not the focus here, and neither is AI work that sits apart from the rest of the engineering. We are looking for someone strong across backend, frontend, infrastructure, and AI integration together.