Job description
We are seeking a highly skilled Technology Engineer specializing in AI/ML Platforms, MLOps, and GenAI infrastructure to design, build, and scale next-generation AI systems.
The ideal candidate will have strong experience in containerized environments, model serving, and cloud-based AI architecture , with a focus on performance, scalability, and resilience.
Key Responsibilities Design, build, and maintain containerized applications using OpenShift, OpenShift AI, Kubernetes, and Helm Charts Deploy and optimize AI inference engines such as Triton Inference Server and vLLM for high-performance model serving Lead end-to-end model lifecycle management , including deployment, monitoring, scaling, and retraining workflows Implement monitoring, logging, and alerting systems using Prometheus and Grafana Collaborate on GenAI and LLM-based projects , including Agentic AI solutions Build and automate CI/CD pipelines using Jenkins, Groovy, Ansible, and Terraform Develop automation scripts and internal tools using Python Architect and manage AI/ML solutions on AWS , leveraging services like SageMaker and Bedrock (preferred) Build and enhance AI platforms across on-premise and cloud environments Ensure systems are highly scalable, fault-tolerant, and performance-optimized Contribute to architecture design, platform roadmap, and strategic technical decisions Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or related field Strong hands-on experience with: Kubernetes / OpenShift ecosystem MLOps and AI/ML deployment pipelines Inference optimization (TensorRT / ONNX / Triton / vLLM) Experience with CI/CD tools (Jenkins, Groovy, Ansible, Terraform) Proficiency in Python scripting and automation Experience with monitoring tools like Prometheus and Grafana Solid understanding of distributed systems, microservices, and cloud-native architecture Hands-on experience with AWS Cloud services (SageMaker, Bedrock preferred) Preferred Qualifications Experience working on GenAI / LLM / Agentic AI use cases Knowledge of GPU acceleration and performance tuning Exposure to hybrid cloud (on-prem + cloud) AI platforms Familiarity with enterprise-scale AI platform engineering What We Offer Opportunity to work on cutting-edge AI/GenAI platforms Exposure to large-scale enterprise AI deployments Collaborative and innovation-driven engineering environment Competitive compensation and growth opportunities
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