Senior Software Engineer, Canoe

• 5+ years of software engineering experience with strong Python backend development
• Experience with relational databases, particularly PostgreSQL, including schema design, query optimization, and migration strategies
• Ability to work with distributed systems and event streaming platforms (Kafka, RabbitMQ, or similar)
• Understanding of API design and microservices architecture patterns
• Experience with cloud platforms (AWS preferred) and containerization (Docker)
• Proficiency with AI-assisted development tools (e.g., GitHub Copilot, Claude Code agent) to accelerate development and testing
• Excellent problem-solving skills with a bias toward pragmatic, maintainable solutions
• Strong communication abilities; comfortable collaborating across teams and documenting technical work
• Experience participating in on-call rotations and production incident response
• Bachelor's degree in Computer Science or related field, or equivalent practical experience

Desirable

• We are looking for a Senior Software Engineer to join our Internal Products team, working on the critical backend systems that power Canoe's document processing and data delivery platform
• You'll design and build scalable microservices, own complex data pipelines, and ensure our systems reliably process millions of alternative investment documents for institutional clients
• Develop and maintain backend services using Python, focusing on document validation, allocation workflows, and human-in-the-loop review systems
• Design and execute database migrations using Alembic and PostgreSQL, ensuring zero-downtime deployments and data integrity
• Build and optimize event-driven architectures using Kafka (AWS MSK) to process high-volume document workflows
• Connect microservices across multiple pods and teams, designing integration points that are resilient and well-documented
• Break down complex features into well-specified tasks and stories, collaborating with product managers and engineering leads
• Propose and implement architectural improvements that enhance system reliability, performance, and maintainability
• Review code and mentor teammates, ensuring high code quality standards and knowledge sharing
• Monitor production systems through Datadog and Splunk, participating in on-call rotation to troubleshoot and resolve incidents
• Deploy solutions to production environments, coordinating with DevOps on infrastructure changes and rollout strategies
• Communicate cross-functionally with engineering pods, product teams, and DevOps to deliver integrated solutions
• Document technical decisions, processes, and runbooks to enable team autonomy and knowledge continuity