AI Infrastructure engineer

Job Description

AI Infrastructure Specialist

About the Role

We are building a next-generation Enterprise AI Platform to power large-scale AI workloads across hybrid environments - and we're looking for an AI Infrastructure Specialist to lead and scale our AI computing ecosystem.

This role will oversee AI workloads across:

. On-prem GPU clusters

. Public cloud platforms

. Private AI cloud environments

. Edge / distributed sites

Key Responsibilities

. Design and manage hybrid AI infrastructure (GPU clusters, Kubernetes, private & public cloud).

. Optimize high-performance compute environments (NVIDIA GPUs, CUDA, NVLink, AI accelerators).

. Enable scalable ML training and inference platforms.

. Implement containerized AI environments and orchestration.

. Support MLOps pipelines and model lifecycle management.

. Enable CI/CD for ML deployments.

. Integrate model registry, artifact storage, and observability tools.

. Manage vector databases and inference endpoints.

. Ensure secure, resilient, and compliant AI infrastructure.

. Drive cost optimization, performance tuning, and capacity planning.

. Support AI use cases such as Generative AI, Vision AI, RAG pipelines, and predictive analytics.

Requirements

. 3+ years in Infrastructure, cloud engineering.

. Hands-on experience with GPU clusters and Kubernetes.

. Strong knowledge of containerization and orchestration platforms.

. Experience operating in hybrid or multi-cloud environments.

. Automation & Infrastructure-as-Code mindset.

. Strong troubleshooting and systems thinking skills.

. Passion for enabling enterprise AI at scale.