Lead Cloud AI Platforms Engineer

12 days ago

Orlando, FL, USAStaff+

Responsibilities

Design and implement cloud infrastructure for LLM platforms, vector databases, and model inference pipelines.
Build and operate scalable environments for agentic AI systems, predictive models, and enterprise AI applications.
Support AI-driven operational use cases including dynamic pricing, demand forecasting, and ramp capacity optimization.
Develop and maintain MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
Develop Infrastructure-as-Code environments using Terraform.
Optimize cloud performance, scalability, reliability, monitoring, logging, and observability for AI and data workloads.
Collaborate with security and compliance teams on data protection, platform security, and regulatory compliance.
Enforce cloud governance, cost optimization, and operational resilience practices.
Design and support edge computing infrastructure for AI capabilities in field operations.
Partner with engineering, data science, and platform teams to integrate AI infrastructure with enterprise systems.

10+ years of experience in cloud engineering, platform engineering, or infrastructure architecture roles.
Strong experience designing and operating containerized environments using Kubernetes and distributed systems architectures.
Experience supporting infrastructure for AI, machine learning, or advanced data platforms.
Experience supporting AI model deployment or inference platforms in operational environments.
Strong knowledge of cloud networking, security architecture, and reliability engineering practices.
Bachelor’s degree in Computer Science, Engineering, or a related technical field.
Preferred experience with LLM platforms, vector databases, and modern AI application architectures.
Preferred familiarity with LangChain, LlamaIndex, Semantic Kernel, OpenAI GPT, Claude, LLaMA, Gemini, OAuth2, and RBAC.
Preferred experience with multimodal AI systems, predictive analytics and data science platforms, edge computing, or field-based AI deployments.
Experience in aviation, logistics, mobility, operational technology, or other regulated industries is preferred.

1,001-5,000 employees