Back End Engineer

About Forma.ai: 

Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. 

Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy.  

We’re welcoming equally driven individuals who are excited about creating something big! 

About the Team

Engineers on this team construct our rules-based calculating engine for processing sales commissions. This might sound simple if you have never been exposed to sales comp plans, it is not! We are low on meetings, high on accountability. Most of the team are in EST time zone but we have a few located in PST and Central as well. We are far from maintenance / progressive evolution in many areas, there is a lot of room to make a big impact in the overall design.

What you’ll be doing

Reporting to the Manager of Data Platform, you will play a critical role in the evolution of our Spark based data platform. You'll lead development efforts for our complex, data-rich platform features while being an example to the team of code quality and thoughtful software design. You will be working on the most challenging code at Forma.

As a Staff Engineer, you are expected to operate with a high degree of ownership and trust. This includes proactively identifying architectural risks, surfacing edge cases or constraints others may not see, and advocating for improvements that strengthen the long-term integrity of the system. We value engineers who bring forward thoughtful perspectives - even when they challenge assumptions - and who help the team see around corners.

You will:

• Design and evolve backend services that power product workflows.
• Architect data models representing hierarchical & graph structures, relationships, and large-scale enterprise datasets.
• Build deterministic, reliable systems that allow customers to reason clearly about their data.
• Drive architectural decisions that balance extensibility, performance, and operational simplicity.
• Improve observability, testing strategy, and production reliability across backend services.
• Partner closely with Product to translate nuanced business requirements into clean, scalable designs.
• Mentor engineers across levels and help raise the bar for backend engineering standards.
• Use, and demonstrate using, AI tooling to improve implementation velocity while thoughtfully investing in technical and product specifications