Senior Backend Engineer, trawa

• You've built complex, data-intensive systems and can point to projects you're proud of
• You've owned a large initiative end-to-end. From fuzzy requirements through an iterative rollout to production - not just the code, but the outcome
• You put the team first: you genuinely enjoy collaborating with people around you and you'd rather support the team than be the lone hero
• You're comfortable making architectural decisions in an evolving codebase
• You're drawn to hard, meaningful problems and want to help shape the next steps of an energy trading and asset-optimization platform
• Don't meet every single requirement? At trawa we are building a diverse, inclusive, and authentic workplace. If you are excited about this role but your background doesn't tick every box, apply anyway — you may be exactly the person we are looking for

Desirable

• You'll join the team that owns energy trading and asset optimization at trawa - the engine that turns market signals and live asset data into smart, automated decisions. It's a data-intensive, high-stakes part of trawa's tech platform where good engineering directly moves the numbers that matter
• We're looking for someone who loves building complex systems, takes real ownership of what they ship, and makes the people around them better. You'll shape architecture, drive initiatives end-to-end, and help define how the team builds
• Designing and building the backend systems behind our trading and asset-optimization platform. The services, data flows, and logic that need to be both fast and dependable
• Owning initiatives end to end: gathering requirements with product and trading colleagues, shaping the approach, and rolling it out iteratively
• Working at the intersection of backend and data - modeling and moving data so it's reliable, explorable, and useful to the people who depend on it, including our data scientists and quantitative traders
• Raising the bar on quality, observability, and how we reason about correctness in a system where mistakes are expensive
• Operating and maintaining what we build. We stay with our systems after launch: keeping them healthy in production, learning from how they behave, and improving them over time
• Our backend is Python-based: we run on AWS with Terraform, and build with FastAPI, Pydantic, and SQLAlchemy. Having worked in this stack is a nice bonus, but not a requirement
• First 6 Weeks - Getting Oriented
• Get up to speed on the trading and asset-optimization systems, our Python/AWS stack (FastAPI, Pydantic, SQLAlchemy, Terraform), and how market and asset data flows through the platform
• Ship your first fixes and small improvements to get familiar with the codebase, our review process, and how we operate in production
• Build relationships with product, data science, and quantitative trading colleagues to understand priorities and how decisions get made
• By Month 3 - Building Momentum
• Take ownership of a meaningful initiative end-to-end: gather requirements, shape the approach, and roll it out iteratively
• Contribute architectural input on at least one active design decision in the codebase
• Help raise the bar on quality and observability by identifying and addressing a gap in how we reason about correctness in production