Senior Software Engineer | AI SaaS Software

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer | AI SaaS Software based in Canada. Join an innovative, remote-first engineering team transforming how software is designed, developed, and delivered through AI-native workflows. As a Senior Software Engineer, you will play a key role in evolving a SaaS platform that helps organizations automate recurring workflows, strengthen compliance, and improve operational efficiency. You will work across backend architecture, frontend development, APIs, and AI-assisted engineering systems, using tools such as Claude Code and Codex to accelerate implementation and problem-solving. Beyond delivering features, you will help redefine how engineers collaborate with AI, build reusable development tools, and improve code quality across the organization. With significant autonomy, minimal meetings, and a focus on outcomes rather than rigid processes, this role offers the opportunity to influence both product direction and engineering culture. You will also have the opportunity to lead a small team and help shape the future of AI-driven software development. \n Accountabilities: Architect, build, and evolve scalable backend systems using Scala, Play Framework, PostgreSQL, Redis, AWS, and related technologies. Design, develop, and deploy reliable APIs and AI-assisted services that support product functionality and business needs. Own end-to-end feature development, from understanding user problems and exploring solutions to implementation, testing, deployment, and production support. Build and maintain frontend experiences using React, Chakra UI, Storybook, Redux, React Query, XState, and other modern development tools. Develop, refine, and maintain agent-driven engineering workflows that support multi-session coding, parallel execution, debugging, and refactoring. Leverage AI coding tools such as Claude Code, Codex, and Cursor to accelerate development while critically evaluating generated code and ensuring maintainability, reliability, and quality. Create internal developer tools, reusable prompts, AI skills, and automation systems that improve engineering productivity and support consistent development practices. Optimize performance across frontend applications, backend services, APIs, infrastructure, and AI-assisted development pipelines. Establish and promote best practices for AI-native software development, including codebase organization, agent interaction, context management, and human-AI collaboration. Take ownership of technical decisions and product outcomes, working with designers, product stakeholders, and engineers to solve problems without relying on detailed specifications or ticket-driven processes. Use dedicated improvement periods to strengthen code maintainability, enhance tooling, explore new technologies, and identify opportunities to improve team effectiveness. Contribute to the evolution of engineering processes through a six-week development cycle followed by a two-week cooldown focused on improvements and experimentation. Progress toward leading a small team of approximately two to three engineers, helping define technical direction, development practices, and effective AI-assisted collaboration. Requirements: At least 7 years of professional software engineering experience, with a strong background in designing, building, and maintaining production systems. Strong backend engineering expertise in Scala or comparable languages such as Java, Ruby, or C#. Solid JavaScript and React experience, with the ability to develop and maintain modern frontend applications. Demonstrated experience building, scaling, and evolving SaaS products in production environments. Deep familiarity with AI-powered coding tools such as Claude Code, Codex, Cursor, or comparable agentic development solutions. Practical experience working with multi-session coding environments and agent-driven workflows, including managing context, coordinating tasks, and guiding long-running coding sessions. Strong judgment in determining when to rely on AI-generated solutions and when manual implementation or deeper investigation is necessary. Experience designing systems and architectures rather than focusing exclusively on implementing individual features. Ability to build or customize AI-assisted development workflows, internal engineering tools, reusable prompts, and agent-based systems that operate across files, repositories, or tasks. Comfort moving between software implementation, system design, AI-agent guidance, debugging, and reviewing generated code. Excellent written communication skills and the ability to collaborate effectively in an asynchronous, distributed team. A self-directed and entrepreneurial mindset, with the ability to prioritize work, make sound technical decisions, and deliver results in ambiguous environments. Strong ownership, adaptability, and a