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.

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 collaborat