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.

Requirements

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