AI Infra Engineer — Hybrid, Production LLM Systems

Hewlett Packard Enterprise Development LP; San Juan, Northern (PR, KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health benefits

Professional development

Inclusion and belonging

Job summary

Hewlett Packard Enterprise is seeking an AI Infra Engineer to design, build, and operate infrastructure that integrates LLMs into internal tools and customer-facing products. You will evaluate third-party tooling, build homegrown pipelines, and own reliability, monitoring, and cost control for AI-powered systems.

The role sits within HPE Networking's Training and Documentation organization and requires a pragmatic, buy-vs-build mindset with strong cloud, container, and scripting skills.

Qualifications

• 5+ years of software engineering, infrastructure, platform, or DevOps/SRE roles.
• Strong scripting/programming ability — Python, Java, etc.
• Experience with cloud infrastructure (AWS, GCP, or Azure) and infra-as-code practices.
• Hands-on experience with containers and container tooling.
• Comfortable operating in Linux and Windows server environments.

Responsibilities

• Design, build, and operate infrastructure that integrates LLMs into internal tools and customer-facing products.
• Evaluate, implement, and maintain third-party AI tooling and platforms, owning vendor relationships and integrations.
• Build homegrown tooling (pipelines, orchestration layers, retrieval systems, evaluation harnesses, monitoring).
• Own the operational reliability of AI-powered systems: uptime, latency, cost, observability.
• Set up monitoring, logging, and telemetry to understand AI system performance in production.
• Collaborate with documentation and training stakeholders to translate use cases into working systems.

Skills

Python

Java

LLM APIs

Cloud infra

Containers

Linux

Windows

Tools

Docker

Kubernetes

Job description

Hewlett Packard Enterprise is seeking an AI Infra Engineer to design, build, and operate infrastructure that integrates LLMs into internal tools and customer-facing products. You will evaluate third-party tooling, build homegrown pipelines, and own reliability, monitoring, and cost control for AI-powered systems.

The role sits within HPE Networking's Training and Documentation organization and requires a pragmatic, buy-vs-build mindset with strong cloud, container, and scripting skills.