Senior Inference Platform SRE & Automation Engineer

Bitdeer Technologies Group; Singapore; On-site; SGD 110,000 - 170,000; Full time

Job summary

Bitdeer Technologies Group seeks an experienced Site Reliability Engineer to own end-to-end reliability of a high-availability inference platform. You will manage API gateways, inference routers, schedulers, and KV caches, ensuring SLA-aligned performance across GPU-backed models and multi-cluster deployments.

The role emphasizes strong Kubernetes operations, Go/Python automation, and robust observability. Collaboration with cross-functional teams and a focus on automation and incident response

Qualifications

• 5+ years in SRE / production platform operations, including 2+ years on a customer-facing API service operating against a published SLA.
• Deep Kubernetes operations experience with multi-cluster topologies.
• Hands-on production experience serving LLM/model inference APIs and complex workloads.

Responsibilities

• End-to-end availability of customer inference endpoints — API availability, request success rate, TTFT/TPOT latency, and the published SLA.
• The serving path: API gateway, inference router, health-based routing, request scheduling, queueing and admission control, prefill/decode serving, and the KV cache service.
• Inference runtime operations: engine health, model load and readiness validation, model revision rollout and rollback.
• Model replica topology and failure isolation across GPUs and NVLink/NCCL.
• Multi-cluster serving across MY/SG/JP with cross-cluster traffic steering and regional recovery.

Skills

Kubernetes

Go or Python

SRE fundamentals

Observability

Incident management

GitOps

Tools

Terraform

Helm

GitOps (ArgoCD/Flux)

Prometheus

Grafana

Job description

Bitdeer Technologies Group seeks an experienced Site Reliability Engineer to own end-to-end reliability of a high-availability inference platform. You will manage API gateways, inference routers, schedulers, and KV caches, ensuring SLA-aligned performance across GPU-backed models and multi-cluster deployments.

The role emphasizes strong Kubernetes operations, Go/Python automation, and robust observability. Collaboration with cross-functional teams and a focus on automation and incident response