Senior AI Platform Engineer: Generative LLMs & Infra

Zerto; San Juan (PR); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Hewlett Packard Enterprise is seeking a Principal Engineer for Generative AI & LLM Platforms. The role operates in a hybrid model, with an expectation to work from an HPE office about two days per week.

The position requires deep experience in AI, ML, and distributed systems, with leadership across multiple teams and a track record of delivering production-grade AI platforms. You will drive architecture, safety, and rapid experimentation at scale.

Qualifications

• Advanced degree in Computer Science, ML, AI or related field.
• At least 15 years of relevant industry experience.
• Proven leadership across multiple teams and architecture ownership.
• Strong hands-on in Python and Golang with APIs and async processing.
• Experience with production-grade Generative AI systems and safety.
• Cloud-native design experience on AWS with infra as code.

Responsibilities

• Technical strategy and multi-year product road mapping.
• Emerging-technology evaluation and customer-focused innovation.
• Production-grade LLM and agentic solution architecture.
• Prompt engineering, fine-tuning, and model customization.
• LLM evaluation, guardrails, privacy, bias, and safety.
• Scalable, low-latency, multi-tenant distributed systems design.
• Observability, SLOs, incident response, capacity and cost management.
• Technical leadership, mentoring, and cross-team influence.
• Agile delivery, rapid prototyping and product ionization.

Skills

Python

Golang

LLMs

AWS

Kubernetes

Distributed systems

Prompt engineering

RAG and agents

Education

Advanced degree in CS/ML/AI

15+ years of experience

Bachelor’s in CS/Engineering/Math

Tools

AWS

Kubernetes

Apache Spark

Flink

pgvector

LangChain

Job description

Hewlett Packard Enterprise is seeking a Principal Engineer for Generative AI & LLM Platforms. The role operates in a hybrid model, with an expectation to work from an HPE office about two days per week.

The position requires deep experience in AI, ML, and distributed systems, with leadership across multiple teams and a track record of delivering production-grade AI platforms. You will drive architecture, safety, and rapid experimentation at scale.