Role overview As a Senior Software Developer with strong Data Engineering and MLOps experience, you design, build, and deliver robust data and machine learning solutions for our clients. You combine strong software engineering habits with hands on experience in data pipelines, cloud environments, automation, model deployment, monitoring, and production ready ML systems. You are comfortable moving between backend development, data engineering, ML lifecycle practices, infrastructure, CI CD, observability, and technical leadership. You collaborate closely with technical and non technical teammates, mentor others, and help teams make sound technical decisions as we deliver enterprise grade AI and data solutions. The technologies below are a reference point for our stack. Above all, we hire for strong fundamentals, judgment, ownership, and growth potential. Your key responsibilities Design, build, and deliver scalable software, data, and machine learning solutions for client projects Identify solutions to cross functional problems using your software development, data engineering, and MLOps experience Design, plan, and implement data pipelines, ML workflows, and supporting cloud or on premise infrastructure Develop end to end solutions aligned with specifications and documentation Build and improve CI CD pipelines, data pipelines, model deployment workflows, and automation practices Contribute to containerized, virtualized, and cloud native environments that support data and ML workloads Support modernization initiatives by improving architecture, testing, deployment, observability, data quality, and maintainability Define, document, and communicate non functional requirements such as performance, reliability, security, scalability, and maintainability Support ML lifecycle practices such as experiment tracking, model versioning, validation, deployment, promotion, rollback, and monitoring Coach colleagues on software development, data engineering, MLOps, and delivery best practices Take initiative, own deliverables end to end, and manage priorities effectively Uphold and strengthen software development guidelines and quality standards Research, test, and implement new techniques, tools, and technologies Advise clients on technical direction, trade offs, architecture, data platforms, and ML solution design The ideal candidate 5+ years of software development experience, including recent hands on experience with data engineering, MLOps, or production ML systems Bachelor’s degree, college degree, certification in a software related field, or equivalent experience Intermediate or conversational French at a minimum Strong backend development experience Strong technical judgment and ability to make pragmatic architectural decisions Experience building or supporting data pipelines, data platforms, or ML deployment workflows Experience collaborating directly with clients or stakeholders Ability to mentor teammates and help raise the quality of technical delivery Comfortable working in ambiguous environments and bringing structure to complex problems You should be proficient with At least one major cloud platform such as AWS, Azure, or Google Cloud At least one major server side programming language such as Python, Java, Node dot js/TypeScript, Go, C, or similar At least one major data engineering platform such as Databricks, Snowflake, BigQuery, Microsoft Fabric, or similar Backend development, API design, and distributed systems Data pipeline orchestration, version control, data validation, feature pipelines, or feature stores ML lifecycle practices such as experiment tracking, model versioning, validation, deployment, promotion, rollback, and monitoring CI CD pipelines and deployment automation Infrastructure as code and provisioning tools such as Terraform, CDK, CloudFormation, Bicep, Ansible, or similar Virtualization and containerization, ideally in a Linux based ecosystem Docker and orchestration tools such as Kubernetes or Docker Compose Microservices, serverless systems, or cloud native architectures Monitoring and observability tooling and services Testing practices such as unit, integration, functional, end to end, or load testing Modern development methodologies such as Agile, Scrum, XP, Kanban, Shape Up, etc. Cloud cost awareness, calculation, and optimization It’s a plus if you have experience with A modern client side framework/library such as React, Angular, Svelte, Vue, Remix, or similar Full stack web development LLMOps, RAG systems, vector databases, or GenAI application deployment Edge computing, IoT, robotics, industrial systems, or hardware adjacent software Simulation environments or developer tooling that improves delivery speed In memory object storage, caching, and queue systems Event driven architecture or messaging systems such as MQTT, Kafka, RabbitMQ, Redis, or similar Hexagonal architecture Domain driven design High availability systems Technical leadership in client facing projects Application security, networking, identity, or compliance considerations What we offer Competitive Salary and contribution to your pension plan (RRSP) Flexible hours of work and choose how you work Work from anywhere up to 8 weeks Paid sabbatical Wellness and productivity spending account Parental program Activities Training And more #J-18808-Ljbffr