AI Systems Engineer

📋 Description

• Architect, build, and optimize production serving pipelines for Small Language Models (SLMs) and
• Own and scale backend microservices (e.g., sds-service-prompt-injection, sds-service-ddr)
• Build consumption-based monitoring, tenant rate-limiting, and runtime guardrail infrastructure.
• Manage and optimize GPU cluster replicas (Kubernetes / Pod infrastructure) to minimize cold-start
• Build continuous evaluation, automated retraining pipelines, model CI/CD, and automated regression
• Refactor legacy service boundaries, service-to-service auth flows, and backend database

🎯 Requirements

• 5+ years of software engineering experience building distributed backend systems or high-throughput
• Proven track record in model serving and inference optimization (e.g., TensorRT, vLLM, ONNX
• Strong programming experience in Python, Go, or C++.
• Hands-on expertise with Kubernetes, container orchestration, GPU scheduling, and infrastructure
• Solid understanding of CI/CD pipelines, MLOps/LLMops principles, and cloud infrastructure (AWS/GCP).