Member of Technical Staff 3

About the Role: We are looking for a Member of Technical Staff 3 to join our Cloud Platform team and contribute to the development, operation, and reliability of our multi-tenant SaaS platform. You will work on backend systems and cloud infrastructure : building features, fixing real production problems, and growing into broader ownership over time. This is a hands-on role with real ownership. You are expected to take a feature or problem end-to-end, write production-quality code, and work closely with more senior engineers on design and architecture. What You Will Do: Engineering & Development - Build and maintain platform components across control plane and data plane - Implement features for tenant provisioning, configuration management, and cluster operations - Write clean, well-tested, production-grade code and participate actively in code reviews - Debug and resolve issues in cloud-native, distributed production environments Operations & Reliability - Partner with SRE on observability, alerting, and incident response for services you own - Improve reliability and operability of platform systems — reduce toil, improve monitoring, fix recurring issues - Contribute to on-call and develop strong instincts for production system behavior Collaboration & Growth - Work closely with senior and principal engineers on design discussions and RFCs - Collaborate with cross-functional teams across geographies - Participate in hiring — conduct interviews and contribute feedback What You Will Bring: Cloud & Infrastructure - 3-5 years of Solid hands-on experience with at least one of AWS, GCP, or Azure — compute, networking, IAM, and managed services - Working knowledge of infrastructure as code — Terraform or equivalent — for provisioning and managing cloud resources - Comfortable working with containerized workloads — Docker, Kubernetes basics (deployments, services, config maps, RBAC, namespaces) Backend Engineering - Strong programming skills in at least one backend language — Go, Java, Python, or equivalent - Experience building and operating REST or gRPC APIs in production - Good understanding of databases — relational and NoSQL — and how to use them reliably at scale Distributed Systems - Practical understanding of distributed systems — service dependencies, failure modes, retries, timeouts, and basic HA patterns - Hands-on with observability — structured logging, metrics dashboards (Grafana, Datadog, or equivalent), and basic alerting; able to diagnose production issues using these tools Security Fundamentals - Awareness of cloud security basics — IAM least-privilege, secrets management, and network access controls AI-Augmented Engineering - Uses AI coding assistants — Claude, Cursor, Copilot — as a regular part of daily workflow for writing, debugging, and reviewing code - Comfortable using AI tools to understand unfamiliar codebases, generate boilerplate, draft documentation, and speed up routine tasks - Knows to review AI output carefully and apply judgment before committing or deploying Good to Haves: - Exposure to Kubernetes operators, controllers, or CRDs - Familiarity with GitOps workflows — ArgoCD, Flux, or equivalent - Basic understanding of multi-tenancy concepts — isolation, resource quotas, or tenant lifecycle - Experience contributing to or building internal observability dashboards and alerting pipelines What Success Looks Like: In 3 months: - Ramped up, productive, and shipping features with guidance - Comfortable with the codebase, deployment process, and team workflow - Engaging actively in code reviews and team discussions In 6 months: - Owning features end-to-end with increasing independence - Reliable on-call contributor — able to diagnose and resolve common production issues - Proactively improving the quality and observability of systems you work on In 12 months: - Trusted, high-output contributor on the team - Beginning to mentor interns or junior engi ... (truncated, view full listing at source)