AI Platform Engineer

Job Description

Role Overview:

An AI Platform Engineer builds and manages the infrastructure and platforms required to develop, deploy, scale, and monitor AI/ML and Generative AI applications.

Key Responsibilities:

Build and maintain AI/ML infrastructure and platforms.
Deploy and scale AI/ML models and LLM applications.
Manage cloud infrastructure using AWS, Azure, or GCP.
Use Docker and Kubernetes for deployment.
Build MLOps and CI/CD pipelines.
Develop APIs and model-serving systems.
Support LLMs, RAG, Vector Databases, and AI Agents.
Monitor AI systems for performance, reliability, security, and cost.
Troubleshoot production AI infrastructure.

Required Skills:
Python
AWS / Azure / GCP
Docker & Kubernetes
Linux & Git
CI/CD
Terraform
MLOps
REST APIs / FastAPI
LLMs & RAG
Vector Databases
Basic AI/ML knowledge
Good to Have
GPU infrastructure
MLflow / Kubeflow
vLLM / KServe
AI security & observability

Experience:
Usually 2–5+ years in Software Engineering, Cloud, DevOps, MLOps, or ML Infrastructure.