Job Description

We are seeking a skilled and motivated Senior AI Infra Engineer to design, develop, and deploy scalable AI infrastructure using MLOps best practices. The ideal candidate will have expertise in PyTorch, TensorRT, Transformers, and KServe to build and optimize Large Language Models (LLMs). Experience with cloud-native AI stack, GPU deployments on Kubernetes (K8s), and agentic frameworks (MCP/A2A) is required.
The successful candidate will have strong programming skills in Python and GoLang, as well as knowledge of Terraform for creating reproducible environments. Familiarity with Retrieval-Augmented Generation (RAG), Vector Databases, API Gateways, and ServiceMesh is a plus.
Please apply, If you have the passion and standard methodologies work in an environment where challenges are a norm, where individual brilliance is valued and goes hand in hand with team performance, Where being proactive is how we do things !!!

Key Responsibilities :

The Senior AI Infra Engineer will be responsible for building and optimizing large-scale AI systems, ensuring scalability, reliability, and performance. The candidate should be able to work collaboratively with cross-functional teams to drive the development and deployment of AI solutions. If you have a passion for building cutting-edge AI infrastructure and are looking for a challenging role, we encourage you to apply. Strong problem-solving skills, attention to detail, and excellent communication skills are essential for this role.

Required Skills and Qualifications :
Expertise in MLOps (pytorch, tensorRT, transformers, Kserve)
AI Infra for inferencing (vLLM, TGI, Triton, Ray Serve), training and fine-tuning LLMs (LoRA/QLoRA)
GPU deployments on K8s
Experience with Agentic frameworks and protocols (MCP/A2A)
Cloud native AI stack (Kubernetes, microservices) with observability and security experience
Python/GoLang expertise and IAC (Terraform knowledge) for creating reproducible env.
Familiarity with RAG/VectorDBs, API Gateways and ServiceMesh

Career Level - IC3

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