Mission Make Phoenix™ & Mythik™ reliable, observable, and production-grade for long‑running AI workflows.

What you’ll do

• Implement distributed tracing across APIs, agents, and tools
• Design metrics, structured logs, dashboards & alerts
• Apply reliability patterns (timeouts, retries, idempotency)
• Support incident readiness & system debugging

What you’ll learn

• How production systems fail—and how to fix them
• Observability best practices used in real platforms
• Designing for long‑running workflows
• Engineering discipline beyond “it works on my machine”

Profile

• Final‑year engineering student (Computer Science, Software, AI, or equivalent)
• Strong Python backend foundations (FastAPI, async, typing)
• Solid understanding of APIs, debugging, and system behavior
• Curious about reliability, performance, and production systems
• Comfortable reading documentation and learning fast