AI / MLOps PLATFORM ENGINEER Industry: IT Services Summary We are seeking an accomplished AI / MLOps Platform Engineer to architect, deploy, and maintain robust infrastructure that powers advanced artificial intelligence and machine learning initiatives. In this pivotal role, you will bridge the gap between data science and production environments, ensuring scalable, secure, and high-performance AI systems. Your expertise will be instrumental in optimizing resource utilization across multi-cloud landscapes, implementing comprehensive observability strategies, and driving operational excellence through automation. This position is critical for enabling the seamless integration of generative AI, agentic workflows, and large language model operations into our core business services. Responsibilities
• Design and implement AI FinOps strategies to monitor, analyze, and optimize cloud spending associated with AI workloads.
• Execute advanced GPU optimization techniques to maximize computational efficiency and throughput for training and inference tasks.
• Manage Site Reliability Engineering (SRE) practices across multi-cloud environments to ensure high availability and fault tolerance.
• Configure and maintain monitoring stacks using Prometheus, Grafana, and Datadog to provide real-time insights into system health and performance.




• Lead incident response efforts and develop automated remediation protocols to minimize downtime and accelerate resolution times.
• Engineer scalable AIOps and MLOps pipelines to streamline the deployment, versioning, and lifecycle management of machine learning models.
• Architect and deploy Generative AI and Agentic AI solutions, including the management of Large Language Model Operations (LLMOps).
• Develop and optimize Retrieval-Augmented Generation (RAG) systems, integrating vector databases and semantic search capabilities for enhanced data retrieval. Requirements

Requirements:
• Minimum of 5 years of skilled experience in IT Services, with a strong focus on platform engineering and DevOps.
• Proven expertise in AI FinOps, GPU optimization, and Multi-Cloud SRE methodologies.
• Proficiency with observability tools such as Prometheus, Grafana, and Datadog for comprehensive system monitoring.
• Hands-on experience in Incident Response management and building operational automation frameworks.
• Deep understanding of AIOps, MLOps, and AI Platform Engineering principles.
• Demonstrated ability to work with Generative AI, Agentic AI, and LLMOps technologies.
• Strong background in implementing RAG architectures, managing vector databases, and configuring semantic search engines.

Salary:
₹25-28 LPA

📌 AI / MLOps PLATFORM ENGINEER (Bengaluru)
🏢 Vrinda International
📍 Bengaluru