Platform & Automation

• Own and scale GKE clusters running production microservices and agent pipelines
• Design and maintain CI/CD pipelines with safe rollbacks and zero-downtime deployments
• Build internal automation and self-service tooling to reduce dependency on manual ops
• Standardize deployment, configuration, and environment management across teams

Data & Storage

• Design and operate replication, backup, and sharding strategies for critical systems
• Optimize storage and metadata systems for large-scale code and graph workloads
• Support distributed data pipelines used in AI and indexing workflows
• Ensure data durability, consistency, and recoverability

Operations & Observability

• Build and maintain robust monitoring, logging, and alerting systems
• Define meaningful metrics and dashboards for system health
• Lead production incident response and write detailed postmortems
• Continuously improve MTTR, availability, and operational maturity

Cost, Security & Leadership

• Actively manage and optimize cloud costs without impacting reliability
• Implement security best practices across infrastructure and pipelines
• Enforce access controls, secrets management, and compliance standards
• Mentor engineers and establish platform engineering best practices

Who We’re Looking For

We’re looking for engineers who have run real systems in production , not just experimented with tools.

• 2+ years building and operating production cloud infrastructure
• Strong hands-on experience with GCP, Kubernetes, and Docker
• Deep understanding of Kubernetes internals, networking, and scheduling
• Proven experience running Service Mesh in production (Istio/Linkerd)
• Strong background in SRE practices : SLOs, SLIs, incident management, postmortems
• Comfortable debugging distributed systems under real pressure
• Solid Linux, networking, and performance-tuning fundamentals
• You think in systems and failure modes, not just scripts and configs

We'd love if

• You’ve built and scaled platforms supporting continuous, long-running workloads
• You’ve measurably improved uptime, latency, or infrastructure costs
• You’ve automated complex, repetitive workflows end-to-end
• You’ve simplified systems while increasing reliability

Why Potpie.ai

• Build AI infrastructure that operates at real scale
• High ownership, minimal bureaucracy
• Strong engineering culture and technical depth
• Opportunity to shape core platform architecture
• Best-in-market compensation and perks

Please note that this is a 6-day WFO role from our office in HSR Layout, Bengaluru. We support relocation within India.