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
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Deploy and optimize AI inference engines such as Triton Inference Server and vLLM for high-performance model serving
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Lead end-to-end model lifecycle management, including deployment, monitoring, scaling, and retraining workflows
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Implement monitoring, logging, and alerting systems using Prometheus and Grafana
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Collaborate on GenAI and LLM-based projects, including Agentic AI solutions
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Build and automate CI/CD pipelines using Jenkins, Groovy, Ansible, and Terraform
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Develop automation scripts and internal tools using Python
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Architect and manage AI/ML solutions on AWS, leveraging services like SageMaker and Bedrock (preferred)
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Build and enhance AI platforms across on-premise and cloud environments
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Ensure systems are highly scalable, fault-tolerant, and performance-optimized
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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
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Strong hands-on experience with:
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Kubernetes / OpenShift ecosystem
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MLOps and AI/ML deployment pipelines
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Inference optimization (TensorRT / ONNX / Triton / vLLM)
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Experience with CI/CD tools (Jenkins, Groovy, Ansible, Terraform)
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Proficiency in Python scripting and automation
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Experience with monitoring tools like Prometheus and Grafana
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Solid understanding of distributed systems, microservices, and cloud-native architecture
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Hands-on experience with AWS Cloud services (SageMaker, Bedrock preferred)
Preferred Qualifications-
Experience working on GenAI / LLM / Agentic AI use cases
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Knowledge of GPU acceleration and performance tuning
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Exposure to hybrid cloud (on-prem + cloud) AI platforms
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Familiarity with enterprise-scale AI platform engineering
What We Offer-
Opportunity to work on cutting-edge AI/GenAI platforms
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Exposure to large-scale enterprise AI deployments
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Collaborative and innovation-driven engineering environment
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Competitive compensation and growth opportunities
