Sr Software Engineer (Product Engineering Background)

Accountabilities: Lead the technical design, architecture, and implementation of major product features and complex engineering initiatives, ensuring scalability, performance, reliability, and maintainability. Own the end-to-end delivery of customer-facing product features, translating business requirements and customer needs into effective technical solutions. Design, build, and improve backend services, APIs, distributed systems, and application architectures. Diagnose and resolve complex engineering challenges, identify technical risks, and improve system performance through monitoring, instrumentation, and data-driven investigation. Leverage AI coding agents to accelerate development, define clear implementation specifications, and rigorously review and validate AI-generated code for correctness, security, and quality. Establish and maintain high engineering standards through code reviews, testing practices, technical documentation, and continuous improvements to development workflows. Mentor engineers, provide architectural guidance, and contribute to technical direction, engineering standards, and knowledge-sharing initiatives. Collaborate with product managers and cross-functional stakeholders to align technical priorities with customer outcomes and business objectives. Take full ownership of production systems and technical initiatives, balancing delivery speed with long-term platform health and operational excellence. Requirements Senior-level experience in software engineering, with a strong background in product engineering and a proven track record of delivering complex production systems. Demonstrated experience owning major product features, technical initiatives, and architectural decisions within scalable software environments. Strong software engineering fundamentals, including backend development, APIs, application architecture, distributed systems, and microservices. Ability to design systems with performance, scalability, reliability, and maintainability in mind. Experience solving complex technical problems and evaluating architectural trade-offs based on measurable customer and business outcomes. Strong technical design, code review, and debugging capabilities, with the ability to assess implementation quality and identify potential risks. Hands-on experience using AI coding agents in everyday development workflows, including defining specifications, directing implementation, and critically validating generated code. Strong understanding of AI-assisted engineering practices and the ability to identify incorrect, incomplete, insecure, or poorly designed AI-generated solutions. Experience working closely with product teams and translating customer problems into effective technical solutions. Proven ability to mentor engineers, influence technical direction, and establish engineering best practices. Excellent communication and collaboration skills, with a proactive, data-driven, and ownership-oriented mindset. Comfortable working in a remote, distributed environment, sharing progress transparently, and making informed decisions independently. Nice to Have: Experience with Node.js, TypeScript, React, or NestJS. Familiarity with RabbitMQ, Kafka, and event-driven architectures. Experience with relational and non-relational databases. Knowledge of AWS, CI/CD pipelines, and modern development workflows. Familiarity with Nx or monorepo development environments. Experience building API-driven products or enterprise software platforms. Previous experience in AI-forward engineering teams using coding agents. Background in EDI, supply chain technology, or B2B data exchange. Benefits Competitive salary: United States: $190,000–$225,000 USD annually. Canada: $190,000–$210,000 CAD annually. Competitive stock options and equity participation. Fully remote working environment across Canada and the United States. Comprehensive health insurance. Unlimited paid time off (PTO). Full-time employment opportunity. Significant technical ownership and influence over architectural decisions. Opportunity to work with AI-assisted development tools in an AI-forward engineering environment. Exposure to large-scale enterprise software supporting hundreds of businesses and millions of transactions. Opportunities to mentor engineers and shape engineering standards within a growing organization.