Software Engineer

Fellow Insights Inc.

14d•CA$110,000 - CA$160,000•Remote

About The Position

Fellow is the AI meeting assistant that helps teams turn conversations into decisions and action, built from the ground up with privacy and security in mind. Recording is one of the most foundational parts of the Fellow experience, and one of the most technically complex. Our platform captures meetings across a wide range of environments, processes real-time audio and video, and turns raw media into the reliable inputs that power everything Fellow helps people do during and after a meeting. You will work on distributed services and media-processing infrastructure that need to operate reliably across thousands of meetings, networks, devices, meeting platforms, and edge cases. The work spans real-time systems, backend services, media pipelines, third-party integrations, and the operational tooling required to run all of it at scale. This is a role for someone who enjoys difficult systems problems, cares deeply about reliability, and likes tracing real-world failures all the way through to durable improvements in the platform. It is also an AI-native role. We use tools like Claude Code and Cursor throughout the development process, and we are looking for an engineer who already works this way: using AI with strong judgment, pushing beyond default workflows, and continually finding better ways to build, test, debug, and operate software.

Requirements

Experience building and operating production-critical systems where reliability, latency, throughput, or consistency materially affect the user experience.
Strong experience with Python or another modern backend language, and the ability to become productive quickly in an unfamiliar codebase.
Strong judgment when balancing delivery speed, system reliability, technical debt, and long-term platform investment.
A track record of owning software beyond implementation, including rollout, observability, production support, and iteration based on real-world behaviour.
Deep, practical use of AI coding agents such as Claude Code, Cursor, Codex, or similar tools, paired with strong judgment and a track record of developing new agentic workflows, tools, or practices that materially improve how software gets built.
Clear communication skills and the ability to collaborate effectively across Engineering, Product, SRE, Support, and other functions.
A willingness to share knowledge, raise the technical bar, and help teammates solve difficult problems together.
Enjoy learning quickly, digging into unfamiliar systems, and staying with a difficult problem until you understand what is really happening.

Nice To Haves

Experience with real-time media, audio or video processing, WebRTC, streaming systems, or similar latency-sensitive infrastructure.
Experience with distributed job processing, event-driven systems, queues, or high-volume asynchronous workloads.
Experience with media tooling or formats such as FFmpeg, codecs, containers, transcoding, or synchronization.
Experience improving observability, incident response, or operational practices for complex production systems.
Experience with Django, Python, GraphQL, Kubernetes, or cloud infrastructure.
Experience working in a high-growth product company or startup environment.

Responsibilities

Build and evolve the services that capture, ingest, and process meeting audio, video, metadata, and real-time events.
Design systems that remain reliable across changing network conditions, platform behaviour, permissions, media formats, and third-party APIs.
Develop tooling and observability that make complex recording failures easier to detect, diagnose, reproduce, and resolve.
Own features and systems through their full lifecycle, from technical design and implementation to rollout, monitoring, and post-release iteration.
Investigate difficult production issues that cross service, infrastructure, media, and integration boundaries.
Work closely with Product, SRE, Support, and other engineering teams to understand real-world situations and turn them into durable platform improvements.
Use AI coding agents deeply in your own workflow, and help create new tools and practices that improve how the team builds software.