Senior Backend Developer, AI Systems

Accountabilities:: Lead the architectural transformation of the core recommendation pipeline into a modern distributed system, delivering incremental improvements while maintaining production stability and reliability. Design, develop, deploy, and operate scalable, fault-tolerant backend services supporting large-scale personalization capabilities, including content selection, send-time optimization, subject line personalization, and frequency capping. Identify, investigate, and resolve performance bottlenecks, reliability issues, and scalability limitations across distributed systems. Collaborate with machine learning engineers and product stakeholders to translate business and technical requirements into robust architectural designs and production-ready solutions. Take end-to-end ownership of critical system components, overseeing architecture, development, implementation, deployment, monitoring, and incident response. Champion engineering best practices across system design, code quality, automated testing, observability, and operational excellence. Contribute to the continuous improvement of distributed infrastructure, ensuring high availability, fault tolerance, and efficient system performance. Provide technical leadership and mentorship to other engineers, encouraging knowledge sharing, sound architectural decisions, and strong engineering standards. Participate in architectural discussions and technical decision-making, helping shape the long-term direction of AI infrastructure and backend systems. Promote a culture of accountability, technical excellence, collaboration, and continuous learning. Requirements: At least 5 years of professional software engineering experience, with a strong focus on distributed systems. Extensive experience designing, building, and operating large-scale distributed systems that are highly available, fault-tolerant, and capable of handling high concurrency. Strong software engineering fundamentals, including system design, unit testing, Git, code reviews, and continuous integration and delivery practices. Strong programming skills in Python and experience developing reliable, maintainable backend services. Experience with distributed data processing frameworks such as Apache Spark, Apache Flink, or Apache Beam. Hands-on experience with Apache Spark is considered an advantage. Solid understanding of distributed systems fundamentals, including consensus, partitioning, replication, back-pressure, idempotency, and failure handling. Practical experience with cloud infrastructure providers such as Google Cloud Platform (GCP), AWS, or Microsoft Azure. Familiarity with modern distributed systems and microservices technologies, particularly Kubernetes, Kafka, and gRPC. Experience with modern software development lifecycle practices, including automated testing, continuous integration, continuous delivery, and automated deployments. Familiarity with containerization and development tools such as Docker, Kubernetes, and GitHub Actions. Strong technical leadership and communication skills, with the ability to influence architectural decisions, collaborate across teams, and mentor fellow engineers. Excellent analytical and problem-solving abilities, particularly when diagnosing and resolving complex issues in production environments. Adaptability, curiosity, and a strong commitment to continuous learning and professional development. Benefits: Competitive annual base salary ranging from CAD 143,000 to CAD 200,000 , depending on relevant experience, technical expertise, and qualifications. Potential additional bonus compensation, depending on the position and final offer. Comprehensive medical, financial, and additional employee benefits. Remote working opportunities within Canada. Opportunity to work on a high-impact AI-powered recommendation engine supporting billions of marketing decisions. Exposure to advanced distributed systems, machine learning infrastructure, and large-scale cloud technologies. Opportunity to influence architectural strategy and contribute to significant technical transformation initiatives. Collaborative environment with experienced engineers, machine learning specialists, and product professionals. Opportunities to develop technical leadership skills and mentor other engineers. Inclusive and diverse workplace culture that values different perspectives, backgrounds, and experiences. Encouragement to apply even if you do not meet every listed qualification, recognizing that transferable skills and diverse experiences bring valuable perspectives to the team.