🛠 Tech Stack

💼 About This Role

You'll own the reliability of AI/ML services in production, ensuring smooth deployment and lifecycle management of models. You'll build observability and automation to drive scalable AI operations. This role directly impacts stability and performance of AI-driven products at scale.

🎯 What You'll Do

• Own reliability, availability, and performance of AI/ML services in production.
• Define and maintain SLOs/SLIs for AI systems.
• Design and implement observability solutions for AI systems.
• Support deployment workflows for ML models including canary and blue/green.

📋 Requirements

• 4+ years of software engineering experience.
• 3+ years in production systems, SRE, DevOps, or platform engineering.
• Strong experience with distributed systems on Kubernetes and cloud platforms.
• Hands-on with Google Cloud Platform services (GKE, BigQuery, etc.).

✨ Nice to Have

• Exposure to AI/ML tooling such as LLM gateways or vector databases.
• Familiarity with ML lifecycle concepts.
• Experience with Terraform for infrastructure-as-code.

🎁 Benefits & Perks

• 🏖️ Fully remote work with structured overlap hours.
• 🏥 Comprehensive health, accident, and retirement benefits.
• 🎓 Exposure to cutting-edge AI/ML infrastructure.
• 📚 Strong culture of learning and collaboration.
• 🌍 Inclusive and globally distributed team environment.

📨 Hiring Process

Estimated timeline: 2-3 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Team Interview· 60 min