This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Platform Engineer based in Canada.
As a Senior Platform Engineer, you will design, build, and operate the backend systems that power a next-generation marketing technology platform.
You will take ownership of critical infrastructure, including query execution, journey orchestration, and data delivery, ensuring reliable and scalable performance as the business grows.
Working across distributed systems, cloud data warehouses, APIs, and real-time data capabilities, you will solve complex engineering challenges with measurable customer impact.
You will play a key role in strengthening platform reliability, security, observability, and operational efficiency while helping shape the evolution of AI-powered marketing products.
This role offers significant autonomy in a fast-paced, founder-led environment where engineers are encouraged to experiment, challenge assumptions, and deliver meaningful results.
You will collaborate with highly technical teammates, contribute to architectural decisions, and help raise engineering standards through mentorship and knowledge sharing.
Ideal for an experienced backend engineer passionate about emerging AI technologies, this opportunity combines technical ownership, continuous learning, and the chance to build systems used by leading global brands.
- Design and develop backend systems: Build, maintain, and operate scalable backend services that move data from cloud warehouse queries to downstream systems, supporting reliable data processing and delivery.
- Optimize platform performance: Improve how services ingest events, execute queries, transform results, and coordinate data delivery, with a focus on correctness, speed, scalability, and operational simplicity.
- Build APIs and integrations: Develop and maintain APIs and integrations across major cloud data warehouses, contributing to the platform's evolution toward real-time data processing and capabilities.
- Own production systems end to end: Take responsibility for services throughout their lifecycle, from design and implementation to deployment, monitoring, maintenance, and incident response.
- Ensure reliability and operational excellence: Participate in the on-call rotation, troubleshoot production incidents, coordinate service restoration, communicate with relevant stakeholders, and implement improvements that prevent recurring issues.
- Strengthen security and observability: Identify and resolve issues affecting platform security, reliability, performance, and maintainability as the infrastructure scales.
- Develop shared engineering tools: Create reusable components, automation, documentation, and developer tools that reduce repetitive work and improve engineering team productivity.
- Leverage AI and emerging technologies: Integrate AI tools into daily engineering workflows to improve development speed and quality, while contributing to the development of machine learning and agentic AI products.
- Collaborate and mentor: Provide thoughtful code reviews, share technical context, mentor fellow engineers, communicate proactively, and help establish engineering practices that support high-quality delivery.
- Drive customer-focused outcomes: Investigate customer challenges, identify practical solutions, and validate their effectiveness through testing, measurement, and continuous improvement.
Requirements
- Professional experience: At least 5 years of professional software engineering experience building, deploying, and maintaining production systems, with strong expertise in Python and backend development.
- Backend and distributed systems expertise: Demonstrated experience designing, building, and scaling backend services and distributed architectures, including ownership of systems throughout their production lifecycle.
- Cloud infrastructure: Experience working with cloud platforms such as Google Cloud Platform (GCP) or Amazon Web Services (AWS), with a strong understanding of scalable infrastructure and cloud-based architectures.
- Reliability and operations: Practical experience with production operations, incident response, on-call responsibilities, observability, troubleshooting, and designing systems for reliability and security at scale.
- API and data systems: Strong knowledge of backend APIs, data processing workflows, and system integrations. Experience with cloud data warehouses, query execution systems, event-driven architectures, or real-time data processing is valuable.
- AI and emerging technologies: A demonstrated interest in adopting advanced technologies, including AI agents and AI-assisted development tools, to improve engineering productivity, software quality, and business impact.
- Startup experience: Experience working in a startup or high-growth environment, with the ability to adapt quickly to evolving priorities and changing technical requirements.
- Problem-solving and ownership: A proactive, resourceful approach to complex engineering challenges, with the ability to identify gaps, clarify requirements, make sound decisions, and drive solutions through to completion.
- Adaptability and continuous learning: Comfort working in ambiguous situations, asking critical questions early, learning new technologies quickly, and adjusting approaches as the business evolves.
- Communication and teamwork: Strong collaboration skills, a willingness to give and receive constructive feedback, and the ability to make teammates more effective through mentoring, documentation, and knowledge sharing.
- Customer and business orientation: A commitment to measurable outcomes, with the ability to connect engineering decisions to customer needs and broader business objectives.
- Independent and collaborative mindset: The ability to thrive in a flexible, relatively flat organization where technical leaders remain hands-on and engineers are trusted to take ownership of meaningful problems.
Benefits
- Competitive compensation: Annual base salary ranging from CAD $160,000 to $175,000, depending on skills, experience, qualifications, and other relevant factors.
- Equity participation: The opportunity to own equity and share in the value created through your contributions.
- Performance recognition: Spot bonuses for significant milestones and major product feature launches.
- Remote-first flexibility: Work remotely within a distributed team spanning North America and other regions.
- Flexible work arrangements: A goal-oriented working environment that emphasizes outcomes, autonomy, and flexibility.
- Flexible time off: Access to flexible paid time off to support personal well-being and work-life balance.
- Company-wide Recharge Days: Monthly days dedicated to disconnecting from work and recharging.
- Home office support: An annual stipend to help create a comfortable and productive remote workspace.
- Comprehensive healthcare: Fully employer-paid health, dental, vision, life, and disability insurance for eligible Canadian employees.
- Retirement savings: Access to an RRSP program with a generous company match for Canadian employees.
- Professional development: An annual development stipend to support continued learning and career growth.
- Innovation and collaboration: Quarterly hackathons that encourage experimentation, creativity, and collaboration on projects driven by team interests.
- Career progression: Clear opportunities for professional advancement and cross-functional collaboration.
- Direct leadership access: The opportunity to work closely with company founders and an experienced executive team.
- Meaningful technical impact: The chance to build and improve AI-powered data and marketing systems used by some of the world's leading brands.
