ML &LLMOps Engineer - 300426-66

Role Summary We are hiring an AI DevOps / LLMOps Engineer to build and operate cloud-native AI platforms and pipelines for production-grade, AI-powered applications. This is a hands-on, ops-focused role requiring deep expertise in Cloud, DevOps, and MLOps/LLMOps, along with the ability to apply AI tools in day-to-day engineering workflows. Must-Have Skills (Non-Negotiable) Cloud & Infrastructure Strong hands-on experience with AWS / Azure / GCP Expertise in Infrastructure-as-Code (Terraform preferred) Experience provisioning and managing production environments MLOps / LLMOps Experience building and operating ML/LLM pipelines Knowledge of: CI/CD for AI workloads Model & prompt versioning Monitoring, drift detection, retraining CI/CD & Platform Engineering Experience designing CI/CD pipelines Automation of build → deploy → monitor workflows Containers & Orchestration Hands-on with Docker and Kubernetes Managing scalable, distributed workloads AI Platform Operations Experience supporting: LLM-based applications (RAG, APIs, pipelines) Vector databases and inference systems Managing compute, scaling, and performance AI-Native Engineering (Critical) Actively uses AI tools (LLMs, copilots, agents) in daily engineering work Experience working with local/open-source LLMs Applies AI to improve automation, debugging, and operational efficiency Core Responsibilities Provision and manage cloud infrastructure for AI applications Build and maintain MLOps / LLMOps pipelines Deploy and operate AI-powered applications in production Implement monitoring, logging, and observability Optimize cost, performance, and resource usage Ensure reliability, scalability, and security Collaborate with engineering teams to productionize AI systems Required Experience 5–10+ years in DevOps / Cloud / Platform Engineering 2–4+ years in MLOps / LLMOps / AI platforms Strong experience with: Python / scripting CI/CD tools Infrastructure-as-Code Preferred Experience with vector databases Exposure to LLM ecosystems Familiarity with microservices / event-driven systems Knowledge of AI governance and security