AI SRE

Southeast Asian tech company building AI infrastructure and large language model products.

Focused on developing AI solutions tailored to regional markets and use cases.

Project/Goal:

Build and maintain infrastructure powering AI applications and model training, supporting workloads reliably and securely at scale across cloud and on-prem environments.

Key Responsibilities:

Build and maintain infrastructure for model hosting, prompt execution, and training workflows.

Operate and optimize model-serving systems (e.g. vLLM, Triton, OpenAI-style proxies).

Implement secure API gateways; manage token usage, routing, and fallback logic.

Develop and support training pipelines, GPU scheduling, and experiment tracking.

Maintain CI/CD systems, observability tooling, and infrastructure documentation.

Skills Requirements:

6+ years in infrastructure engineering, DevOps, or ML systems.

Strong command of Kubernetes, Terraform, and cloud-native architecture (AWS/Azure/GCP).

Experience with containerization, CI/CD, and API security practices.

Prior exposure to model hosting or ML pipeline orchestration.

Understanding of networking (VPNs, VNets, hybrid connectivity) and cross-platform security best practices.

Experience with on-prem infrastructure (networking, storage hardware).

Good to Have:

GPU resource orchestration or Kubeflow experience.

Familiarity with inference servers (vLLM, Triton, TGI, TorchServe).

Cost telemetry / resource budgeting for model traffic.

Security mindset — IAM, logging, compliance experience.

Familiarity with compliance frameworks (SOC2, GDPR, HIPAA).

Background in database management across platforms.

Work Location:

Mid-to-senior level, 6+ years relevant experience.