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.Ai: 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.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! 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.

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.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.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 specificationsWhat We're Looking for: Significant experience designing and building complex backend systems in production environments.Demonstrated ability to surface unarticulated risks, propose alternative approaches,



and advocate for architectural improvements with sound technical reasoning.Expertise in at least one production-grade backend language (e.Python, Java, Kotlin, Go, C#, etc.).Strong foundation in relational schema design, data modelling, and SQL.Background working with Spark, or other ETL tools / frameworksExperience working with hierarchical, graph-like, or relationship-heavy data structures.Familiarity with graph databases or graph-based modelling concepts is a strong plus.A track record of improving scalability, reliability, and observability in distributed or data-intensive systems.Thrive in a collaborative, detail-oriented environment across Engineering, Product, and Analytics.Experience building SaaS products serving mid-market or enterprise customers.Experience building rule-driven systems, validation workflows, or approval/governance platforms.Familiarity with AWS-based infrastructure and Kubernetes.Exposure to Sales Performance Management (SPM), RevOps, Incentive Compensation (ICM), or related domains.Frontend: JavaScript, React, TypeScriptBackend: Java/Springboot, Django, PostgresInfrastructure: AWS, DockerWhat success looks like: 30/60/90 days You’ll focus on building deep context across the product domain, backend architecture, and the data models that power Forma’s platform.Ai’s product, customers, and sales performance domain.Built a clear mental model of the backend architecture, core services, and data flows across the system.Gained familiarity with key data models, including hierarchical structures, relationships, and workflow-driven entities.Learned the team’s engineering practices around testing, observability, deployment, and reliability.Built relationships with engineering, product, and analytics partners.Contributed to technical discussions, asking thoughtful questions and identifying early areas of complexity or risk.Shipped small but meaningful improvements or fixes to build familiarity with the system.Started identifying opportunities to improve data modeling, system clarity,



or backend reliability.You’ll begin owning meaningful backend systems and influencing technical decisions.Demonstrated robust judgment in data modeling, especially around relationships, hierarchy, and workflow representation.Identified and surfaced architectural risks, edge cases, or inconsistencies in existing systems.Proposed and, where appropriate, implemented improvements to backend architecture, data models, or service boundaries.Contributed to improvements in observability, testing, and production reliability.Participated actively in code reviews and technical design discussions, raising the bar for quality and clarity.Built enough system context to make informed tradeoffs between performance, extensibility, and simplicity.You’ll be operating as a trusted technical leader across backend systems.Introduced or significantly improved core data models, system architecture, or workflow handling.Demonstrated the ability to anticipate and mitigate long-term architectural risks.Influenced technical direction through clear, well-reasoned proposals and design decisions.Established strong working relationships across Engineering, Product, and Analytics.Elevated engineering standards through mentorship, design reviews, and technical guidance.Helped the team better reason about complex, data-intensive workflows through clearer system design.Identified and begun executing on longer-term backend investments that improve system integrity and developer velocity.Demonstrated clear impact on both system quality and the team’s ability to deliver confidently at scale.Ai’s success.Healthcare coverage. We have a full benefits package that includes medical, dental, vision, disability and life insurance, and a paid parental leave program.Access the resources you want to help you grow in your role by utilizing our $750 yearly training stipend.We have kids and pets.

Mortgages and student loans. Love our customers. Our platform solves a very complex problem in a currently underserved market. While everyone at Forma isn’t customer-facing, we’re all customer-focused.

Maybe even slightly customer-obsessed.Use of AI for Recruitment Ai does not use artificial intelligence as part of our recruitment process, specifically but not limited to the screening, filtering and shortlisting of applicants.

📌 Staff Back End Engineer (Data Platform) (Winnipeg)
🏢 Forma.ai
📍 Winnipeg