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Rootly

Verified Job Source

AI-powered on-call and incident response. Trusted by leading companies like NVIDIA, Squarespace, Canva, Figma, and more.

Toronto, Ontario

Software Development
51–200 people

About

AI-native on-call and incident response. Modern Slack and MS Teams native incident management—from your first alert to retrospective. Trusted by 100s of leading companies including NVIDIA, Squarespace, Canva, Grammarly, Elastic, Tripadvisor, and Figma. See why they rate us 5 stars on G2: https://www.g2.com/products/rootly-manage-incidents-on-slack/reviews

Open positions

Engineering Manager

Remote · Canada

You will lead and scale a high-performing team of remote engineers while setting the technical vision and roadmap for the product. Additionally, you will be responsible for hiring, mentoring, and fostering a culture of collaboration and accountability within the engineering department.

Forward Deployed Technical Product Manager

On-site

You will own the product strategy, build a prioritization framework, and lead the product management team to achieve long-term growth goals. You will work closely with engineering, GTM, and leadership to ensure accountability and clear execution of the product vision.

Member of Technical Staff, Intern

Hybrid · Toronto

You will manage the SRE Skills Bench open-source project by designing evaluation scenarios and expanding datasets for AI reliability testing. Additionally, you will collaborate with researchers and engineers to analyze results and promote the benchmark within the AI and reliability communities.

Enterprise Account Executive (Bay Area)

Hybrid

Build a book of business across North America and close enterprise software deals ranging from $50K to $150K+ ARR. Collaborate with company leadership to refine the sales process and present product narratives to executive stakeholders.

AI Quality Engineer

On-site

Own the evaluation and optimization of agentic AI features by designing test scenarios and running adversarial prompts. Collaborate with engineering and product teams to identify failure modes and track quality metrics to improve AI performance.