DCG

AIOps Engineer

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SeniorZdalnie·WarszawaFull-time

#457904·Dodano 22 dni temu·6

Źródło: nofluffjobs.com

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Tech Stack / Keywords

OpenShift KubernetesGPUAIMLOpsLLM Python Linux Azure

Firma i stanowisko

DCG is a recruitment company focused on partnering with experienced professionals and providing continuous support. The role is part of ongoing recruitment projects to serve business needs.

Wymagania

5+ years of experience in DevOps, Site Reliability Engineering (SRE), Platform Engineering, or Infrastructure Operations
At least 2 years of hands-on experience supporting MLOps, AI Infrastructure, or Large Language Model (LLM) platforms
Strong experience with Kubernetes and OpenShift administration in production environments
Proven experience deploying and operating vLLM-based inference platforms in production
Strong understanding of LLM serving concepts including Paged Attention, continuous batching, and inference optimization techniques
Deep knowledge of NVIDIA GPU technologies, CUDA drivers, NVIDIA Container Toolkit, and GPU troubleshooting
Hands-on experience with Prometheus, Grafana, OpenTelemetry, and ELK Stack
Experience building observability solutions with custom metrics, exporters, dashboards, and alerting
Strong Python programming skills for automation and operational tooling
Experience with Bash scripting and Linux systems administration
Familiarity with GitLab CI, Jenkins, ArgoCD, and Infrastructure-as-Code practices
Strong analytical and problem-solving skills for complex distributed environments
Excellent communication and collaboration skills

Obowiązki

Design, deploy, and maintain vLLM inference services on OpenShift/Kubernetes running on bare-metal GPU infrastructure
Manage NVIDIA GPU resources, including GPU partitioning and allocation
Automate model lifecycle management, including model onboarding, versioning, deployment, hot-swapping, and rollback from private registries
Implement and manage Horizontal Pod Autoscaling (HPA) based on workload demand, queue depth, and GPU utilization
Optimize vLLM configurations and serving parameters for performance and efficiency
Build and maintain observability and monitoring solutions including metrics collection, logging, and tracing
Instrument vLLM endpoints with metrics for token consumption, latency, throughput, and error rates
Develop usage tracking mechanisms for quota management and chargeback/showback
Create and maintain Grafana dashboards for infrastructure, GPU utilization, inference performance, and business metrics
Configure proactive monitoring and alerting using Prometheus and Alertmanager
Implement and maintain API Gateway solutions for authentication, authorization, rate limiting, and routing
Ensure secure operation through network segmentation, ingress/egress controls, and adherence to security best practices
Maintain audit logging to support compliance and operational governance
Collaborate with AI Engineering, Platform Engineering, Security, and Infrastructure teams

Benefity

Private medical care
Co-financing for the sports card (sport subscription)
Training and learning opportunities
Constant support of a dedicated consultant
Employee referral program

Opieka zdrowotna

Karta sportowa

DCG

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