Senior Software Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Enhance current enterprise applications by creating new user interfaces and RESTful APIs that deliver AI-driven functionalities to clients.

• Collaborate with ML engineers, UX designers, and product managers to convert model outputs and user needs into production-ready features.

• Take ownership of features from start to finish, encompassing database and API design through to front-end development and deployment.

• Spot opportunities for enhancing system architecture, performance, and scalability across the ML platform.

• Develop internal tools for deploying, testing, monitoring, and managing ML models and pipelines.

• Promote engineering best practices, including conducting code reviews, establishing testing strategies, maintaining documentation, and mentoring junior engineers.

• Partner with quality engineering teams to enhance automated testing processes and application reliability.

• Engage in technical roadmap discussions and align architectural decisions with business objectives.

• Operate both independently and collaboratively within the team.

⛳️ Requirements

• A university degree or equivalent qualification in Computer Science, Software Engineering, or a related discipline.

• Over 7 years of professional experience in software development.

• Strong expertise in at least one back-end programming language; experience with Ruby/Rails is advantageous; Python is utilized.

• A willingness and eagerness to learn new programming languages and frameworks.

• Significant experience in designing, building, and consuming RESTful APIs.

• Proficiency in modern front-end frameworks such as React, Vue, or Angular.

• Knowledge of front-end performance optimization best practices.

• Strong SQL development capabilities.

• Experience with relational database systems.

• Familiarity with source control tools like Git.

• Experience with contemporary branching, pull request, and code review processes.

• Exposure to Agile development methodologies.

• Familiarity with ML workflows, whether by collaborating with data scientists, integrating model APIs, or developing ML-adjacent tools.

• Knowledge of LLM-based systems and ML frameworks.

• Understanding of the Model Context Protocol (MCP).

• Experience with cloud data warehousing and analytics engineering, especially with Snowflake and dbt.

• Experience in cloud environments such as AWS.

• Proficiency with containerization technologies like Docker and Kubernetes.

• Familiarity with CI/CD pipelines and DevOps practices.

🏝️ Benefits

• A trusted, empowered, and supportive work environment.

• Opportunities for growth.

• Tools necessary for success.

• Collaborative team support.

• Outcomes prioritized over hours worked.

• Curiosity appreciated over perfection.

• Collaboration emphasized over ego.