Devops Engineer

JOB DESCRIPTION

One of our largest Telecom customers is seeking a skilled DevOps Engineer to join their Data Platform team within the Chief Data Office.

• This Engineer will play a key role in building, operating, and scaling a production-grade AI inferencing platform that supports high-throughput, low-latency large language model (LLM) workloads.
• The position combines software engineering, platform engineering, and reliability engineering responsibilities, with a focus on developing Python-based services, automating model deployments, and optimizing model serving performance using vLLM, Kubernetes, KServe, and Knative.
• The engineer will be responsible for containerization with Docker and Podman, maintaining and tuning PostgreSQL data models, troubleshooting production issues, and driving platform reliability through observability and automation.
• Working closely with ML engineers and platform architects, this individual will help scale mission-critical AI services, support new model rollouts, and continuously improve the infrastructure that powers enterprise AI applications.

REQUIRED SKILLS AND EXPERIENCE

• Strong hands-on python coding & development experience as well as experience working with FastAPI
• Expertise with Docker & Kubernetes, including deployments, services, autoscaling, and troubleshooting workloads in production.
• Practical experience with Postgres, including query optimization and schema design.
• Cloud platform experience, such as Azure/AKS, AWS/EKS, or Google Cloud Platform/GKE.
• Strong debugging skills across the stack — from application code to infrastructure
• NICE TO HAVE SKILLS AND EXPERIENCE
• Direct experience with vLLM or LLM inferencing
• Experience with GPU-aware scheduling and resource management in Kubernetes.
• Familiarity with LLM-specific optimizations: speculative decoding, quantization (FP8/INT8), KV cache management, and continuous batching.
• Experience with API gateways or LLM routing layers, such as LiteLLM or similar.
• Background in SRE practices: SLOs/SLAs, incident response, and on-call tooling.
• Experience with Helm, ArgoCD, or other GitOps deployment tooling.