About the role

Software Engineer building reliable recording and media-processing infrastructure for Fellow, an AI meeting assistant. Developing distributed services, observability, and AI-native engineering workflows.

Responsibilities

Build and evolve services that capture, ingest, and process meeting audio, video, metadata, and real-time events
Design reliable systems across changing network conditions, platform behaviour, permissions, media formats, and third-party APIs
Develop tooling and observability to detect, diagnose, reproduce, and resolve complex recording failures
Own features and systems through technical design, implementation, rollout, monitoring, and post-release iteration
Investigate production issues spanning services, infrastructure, media, and integrations
Collaborate with Product, SRE, Support, and engineering teams to turn real-world situations into platform improvements
Use AI coding agents and help create tools and practices that improve software development
Learn unfamiliar systems quickly and investigate difficult problems through to durable solutions

Experience building and operating production-critical systems where reliability, latency, throughput, or consistency materially affect user experience
Strong experience with Python or another modern backend language
Ability to become productive quickly in an unfamiliar codebase
Strong judgment balancing delivery speed, system reliability, technical debt, and long-term platform investment
Track record of owning software through rollout, observability, production support, and real-world iteration
Deep practical use of AI coding agents such as Claude Code, Cursor, Codex, or similar tools
Track record of developing agentic workflows, tools, or practices that materially improve software development
Clear communication and effective collaboration across Engineering, Product, SRE, Support, and other functions
Willingness to share knowledge and help teammates solve difficult problems
Nice to have: experience with real-time media, audio/video processing, WebRTC, streaming systems, or latency-sensitive infrastructure
Nice to have: distributed job processing, event-driven systems, queues, or high-volume asynchronous workloads
Nice to have: FFmpeg, codecs, containers, transcoding, or synchronization
Nice to have: observability, incident response, or operational practices for complex production systems
Nice to have: Django, Python, GraphQL, Kubernetes, or cloud infrastructure
Nice to have: experience in a high-growth product company or startup environment
Candidates must be located in Canada

Remote-first work arrangement
Optional office space available in Ottawa, Montreal, and Toronto
Flexible collaboration supported by core hours from 10 a.m. to 4 p.m. Eastern Time
Equal employment opportunities
Accommodation during any stage of the recruitment process