Job Description:

Responsibilities:

Build and maintain containerized applications using OpenShift, OpenShift AI, Kubernetes, and Helm charts.
Integrate and optimize inference engines such as Triton and vLLM for scalable model serving.
Lead model deployment, monitoring, and lifecycle management in production environments.
Implement monitoring and alerting solutions using Grafana and Prometheus.
Collaborate on GenAI and LLM projects, including Agentic AI initiatives.
Automate CI/CD pipelines and infrastructure using Jenkins, Ansible, Groovy, and Terraform.
Develop automation scripts and tools in Python.
Architect, deploy, and manage AI/ML solutions on AWS Cloud; experience with Bedrock and SageMaker is a plus.
Build and enhance AI Platform ( both on premise and in public cloud).
Make is scalable, high performance and resilient
Contribute to future road map and key architecture decisions

Requirements:

Strong skills in OpenShift, OpenShift AI, Kubernetes, Helm, and container orchestration.
Hands-on experience with inference engines (Triton, vLLM) and model serving.
Proficiency in model deployment, monitoring, and MLOps best practices.
Familiarity with Grafana, Prometheus, Jenkins, Ansible, Groovy, Terraform, and Python.
Understanding of GenAI, LLMs, and Agentic AI concepts.
Experience with AWS Cloud services; Bedrock and SageMaker knowledge is desirable.

Excellent problem-solving and communication skills

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