
51 - 200 employees
Founded 2017
đ€ Artificial Intelligence
âïž SaaS
đą Enterprise
đ° $24M Series A on 2021-11
Artificial Intelligence âą SaaS âą Enterprise
Fellow is an AI meeting assistant and secure note-taking platform that records, transcribes, and summarizes meetings across Zoom, Google Meet, Microsoft Teams, Slack huddles, and in-person sessions. Built with a privacy-first approach, Fellow emphasizes enterprise-grade security and governance (SOC 2 Type II, HIPAA, GDPR), never trains its AI on customer data, and offers granular controls like role-based access, zero-day retention, MNPI redaction, and exam-ready audit logs for regulated industries. The product includes an AI agent (AskFellow) to surface meeting insights, generate follow-ups and documents, and automate CRM and project-tool updates; it centralizes recordings and integrates with 50+ tools (Salesforce, HubSpot, Asana, Jira, Notion, Slack, etc. ). Fellow is positioned for enterprise and regulated teamsâfinance, legal, healthcareâseeking secure, centralized meeting intelligence.
đ August 5
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51 - 200 employees
Founded 2017
đ€ Artificial Intelligence
âïž SaaS
đą Enterprise
đ° $24M Series A on 2021-11
Artificial Intelligence âą SaaS âą Enterprise
Fellow is an AI meeting assistant and secure note-taking platform that records, transcribes, and summarizes meetings across Zoom, Google Meet, Microsoft Teams, Slack huddles, and in-person sessions. Built with a privacy-first approach, Fellow emphasizes enterprise-grade security and governance (SOC 2 Type II, HIPAA, GDPR), never trains its AI on customer data, and offers granular controls like role-based access, zero-day retention, MNPI redaction, and exam-ready audit logs for regulated industries. The product includes an AI agent (AskFellow) to surface meeting insights, generate follow-ups and documents, and automate CRM and project-tool updates; it centralizes recordings and integrates with 50+ tools (Salesforce, HubSpot, Asana, Jira, Notion, Slack, etc. ). Fellow is positioned for enterprise and regulated teamsâfinance, legal, healthcareâseeking secure, centralized meeting intelligence.
âą Build and evolve services that capture, ingest, and process meeting audio, video, metadata, and real-time events âą Design reliable systems across changing network conditions, platform behaviour, permissions, media formats, and third-party APIs âą Develop tooling and observability to detect, diagnose, reproduce, and resolve complex recording failures âą Own features and systems through technical design, implementation, rollout, monitoring, and post-release iteration âą Investigate production issues spanning services, infrastructure, media, and integrations âą Collaborate with Product, SRE, Support, and engineering teams to turn real-world situations into platform improvements âą Use AI coding agents and help create tools and practices that improve software development âą Learn unfamiliar systems quickly and investigate difficult problems through to durable solutions
âą Experience building and operating production-critical systems where reliability, latency, throughput, or consistency materially affect user experience âą Strong experience with Python or another modern backend language âą Ability to become productive quickly in an unfamiliar codebase âą Strong judgment balancing delivery speed, system reliability, technical debt, and long-term platform investment âą Track record of owning software through rollout, observability, production support, and real-world iteration âą Deep practical use of AI coding agents such as Claude Code, Cursor, Codex, or similar tools âą Track record of developing agentic workflows, tools, or practices that materially improve software development âą Clear communication and effective collaboration across Engineering, Product, SRE, Support, and other functions âą Willingness to share knowledge and help teammates solve difficult problems âą Nice to have: experience with real-time media, audio/video processing, WebRTC, streaming systems, or latency-sensitive infrastructure âą Nice to have: distributed job processing, event-driven systems, queues, or high-volume asynchronous workloads âą Nice to have: FFmpeg, codecs, containers, transcoding, or synchronization âą Nice to have: observability, incident response, or operational practices for complex production systems âą Nice to have: Django, Python, GraphQL, Kubernetes, or cloud infrastructure âą Nice to have: experience in a high-growth product company or startup environment âą Candidates must be located in Canada
âą Remote-first work arrangement âą Optional office space available in Ottawa, Montreal, and Toronto âą Flexible collaboration supported by core hours from 10 a.m. to 4 p.m. Eastern Time âą Equal employment opportunities âą Accommodation during any stage of the recruitment process
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