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RCV Innovations Pvt Ltd

Job Description ​We are seeking a highly skilled and hands-on AI Infrastructure Engineer to design, build, and maintain our next-generation, self-hosted AI infrastructure. In this role, you will bridge the gap between enterprise infrastructure and advanced AI engineering. You will be responsible for deploying, optimizing, and orchestrating multi-model Large Language Models (LLMs), Vision-Language Models (VLMs), and Agentic AI frameworks on both raw bare-metal hardware and enterprise container platforms.​The ideal candidate thrives in a high-performance computing environment, understands the nuances of bare-metal GPU clustering, and has a proven track record of moving open-source AI stacks from experimental setups into secure, scalable production environments.​Key Responsibilities​1. AI Infrastructure &amp; Deployment Orchestration<ul><li>​Design, provision, and manage high-performance compute clusters on bare-metal (Rocky Linux / Ubuntu) and enterprise platforms (Red Hat OpenShift / Kubernetes).</li><li>​Deploy, optimize, and maintain scalable LLM/VLM serving engines using vLLM and Ollama, ensuring low-latency and high-throughput inference.</li><li>​Configure and scale distributed training and inference workloads using Ray framework, specifically optimizing for multi-GPU, multi-modal applications (Text, Image, and Audio).</li><li>​Set up, secure, and customize enterprise-grade user interfaces like Open WebUI for cross-functional team access.</li></ul>​2. Advanced RAG &amp; Model Lifecycle Management<ul><li>​Architect and maintain end-to-end Retrieval-Augmented Generation (RAG) pipelines with advanced context management, chunking strategies, and hybrid search capabilities.</li><li>​Integrate and tune vector databases (e.g., Milvus, Qdrant, PGVector) to support high-context RAG operations.</li><li>​Establish reproducible pipelines for model fine-tuning (PEFT, LoRA, QLoRA) on private datasets, optimizing memory efficiency and training times.</li></ul>​3. Agentic AI &amp; Autonomic Systems<ul><li>​Design and deploy scalable Agentic AI frameworks (e.g., CrewAI, AutoGen, LangGraph) capable of executing multi-step complex workflows, tool use, and self-correction.</li><li>​Develop custom agent &quot;skills&quot;, API integrations, and secure sandboxed execution environments for autonomous agents.</li></ul>​Required Technical Skills​Core AI &amp; MLOps Stack<ul><li>​Inference Engines: vLLM (including tensor-parallel/pipeline-parallel setups), Ollama, Hugging Face TGI.</li><li>​Distributed Computing: Ray (Ray Train, Ray Serve, Ray Core).</li><li>​Frameworks &amp; UIs: Open WebUI, LangChain, LangGraph, CrewAI, AutoGen.</li><li>​Data &amp; RAG: Advanced RAG architecture, semantic chunking, metadata filtering, and vector database administration.</li><li>​Fine-Tuning: DeepSpeed, Axolotl, or standard PyTorch-based fine-tuning workflows utilizing LoRA/QLoRA.</li></ul>​Infrastructure &amp; System Engineering<ul><li>​Orchestration: Advanced Kubernetes administration, Red Hat OpenShift, Helm charting, and K8s operators (specifically NVIDIA GPU Operator).</li><li>​Operating Systems: Expert-level administration of Linux distributions (Rocky Linux / RHEL, Ubuntu Server).</li><li>​Hardware &amp; Networking: Deep understanding of bare-metal GPU nodes (NVIDIA H100, L40S, A100), PCIe topologies, NVLink, and high-speed networking (InfiniBand/RoCE, SR-IOV).</li><li>​Containers: Docker, Podman, and secure container runtimes (CRI-O, containerd).</li></ul>Pay: ₹15,000.00 - ₹40,000.00 per monthBenefits:<ul><li>Provident Fund</li></ul>Work Location: In person

AI Infrastructure Engineer

Join RCV Innovations Pvt Ltd and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

RCV Innovations Pvt Ltd

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AI Infrastructure Engineer