The Role

Firetiger’s agents find production problems before your CEO hears about them, and avoids burning engineering time on investigation and remediation.

Step 1: Store telemetry with unprecedented detail.

Step 2: Agents set up the right monitors.

Step 3: Agents identify root cause and remediate problems.

You'll be a product engineer focused on the interfaces between humans and AI agents—building the workflows, visualizations, and interaction patterns that make complex autonomous technical operations workflows intuitive and actionable for engineering teams.

What You'll Build

Investigation interfaces: Design how engineers interact with AI agents conducting real-time root cause analysis across their systems. What should an autonomous investigation look like? How do you present complex findings clearly?

The agents themselves!: Create intuitive ways for humans to define monitoring objectives in natural language and build the brains that turn those messy inputs into the crisp outputs our customers rely on to run their businesses.

Real-time collaboration tools: Build interfaces where engineers can watch agents work, redirect investigations, and collaborate on complex debugging sessions.

Interactive debugging experiences: Design new UX patterns for exploring high-cardinality data that agents surface—think beyond traditional dashboards to novel ways of understanding customer-specific issues.

Sample Projects

• Build a live investigation viewer where engineers watch agents correlate signals across their stack
• Design workflow builders that let teams define "customer success" criteria and see immediate agent feedback
• Create interactive timeline views that show how code changes cascade through customer experiences
• Implement real-time collaboration features for teams debugging complex incidents with agent assistance
• Run A/B tests on investigation presentation to optimize how quickly engineers can act on agent findings

The Company

Founded by Rustam (ex-Cloudflare) and Achille (ex-Segment), who experienced firsthand the limitations of traditional observability tools at while operating mission-critical software at hyperscale.