СингапурPlatform Support Engineer (Singapore)
1 мес. назад
СингапурRemote
awsazuregcpcloud infrastructure
Technical customer-facing support for hybrid and self-hosted deployment infrastructure and performance issues on AWS, Azure, and GCP.
О компании
- is the agent observability platform. By actively applying intelligence to agent traces and automatically surfacing the most critical patterns, gives teams the visibility to understand how agents behave in production and the tools to improve them. Teams at Notion, Stripe, Box, OpenAI, and Cloudflare use to trace their agents, find the issues in their observability data, and run evals that tell them how to improve.
Обязанности
- Our largest customers don't just use — they run it. They deploy our stack inside their own AWS, Azure, and GCP accounts, behind their own VPCs, under their own compliance requirements, at their own scale. When a hybrid deployment stalls, when ingest backs up, when a query that was fast last week isn't, they come to us. Platform Support is the team that owns that. We're the technical front line for infrastructure, performance, and reliability.
- We're hiring Platform Support Engineers at both mid and senior levels to join a small, high-ownership team. You'll work shoulder to shoulder with our Cloud Infrastructure and Engineering teams, and alongside our Developer Support Engineers, who own the SDK and API side of the customer experience. If you like hard infrastructure problems, and you like them more when a real customer is on the other end, this is the role.
- Own customer-facing support for hybrid and self-hosted deployments across AWS, Azure, and GCP — from first install through steady-state operation.
- Debug real infrastructure problems: Kubernetes workloads, Terraform state, networking and VPC configuration, IAM and permissions, TLS, and cloud-provider quirks.
- Diagnose performance and reliability issues in the backend — ingest throughput, query latency, database and object-store behavior — using logs, metrics, and traces to get to cause rather than symptom.
- Lead incident response for customer-impacting issues: triage, communicate clearly while it's still on fire, and drive it to resolution.
- Ship fixes. Submit PRs to our backend services, Terraform modules, and deployment tooling rather than handing every problem to Engineering.
- Build the tooling that makes the next one easier — diagnostics, health checks, preflight validation, and self-service paths that let customers unblock themselves.
- Write and maintain the runbooks and deployment documentation that turn one hard-won answer into a permanent one.
- Feed patterns back to Engineering and Product, so the recurring failure modes stop recurring.
- Participate in an on-call rotation for critical customer issues.
Требования
- Experience in a customer-facing technical role — Support Engineering, SRE, DevOps, Solutions Architecture, or Infrastructure Engineering — or backend/infra engineering experience with real appetite for customer work.
- Strong Kubernetes fundamentals: you can deploy, debug, and scale actual workloads, and read a failing pod's story from its events and logs.
- Hands-on Terraform, and depth in at least one major cloud (AWS strongly preferred).
- Comfort in a backend codebase — Python, TypeScript, or Go — enough to reproduce a bug, trace it to its source, and fix it.
- Fluency with observability tooling, and the instinct to reach for data before opinion.
- Clear, calm, direct communication under pressure, especially when the customer is technical, blocked, and losing time.
- Ownership. You take a problem personally and follow it until the customer is running again.
Будет плюсом
- Supporting self-hosted or on-prem enterprise software, especially in regulated environments.
- Multi-cloud experience, particularly Azure or GCP alongside AWS.
- Database and data-infrastructure depth — Postgres, ClickHouse, or similar analytical stores.
- Experience with observability, ML infrastructure, or developer platforms.
- Familiarity with LLM APIs and how teams are building and evaluating agents in production.
- Having built support or diagnostic tooling that measurably reduced ticket volume.
Условия
- Work on genuinely hard infrastructure problems, at the scale and pace of the teams building the best AI products in the world.
- Join a team early enough to shape how it operates — its standards, its tooling, and its bar.
- Sit close to both the customer and the code, with the mandate to fix things in either direction.
- Medical, dental, and vision insurance
- Daily lunch, snacks, and beverages
- Flexible time off
- Competitive salary and equity
- Wifi & cellphone stipend