Principal Engineer - Generative AI & LLM Platforms

About the role

Hewlett Packard Enterprise is hiring a Principal Engineer for Generative AI and LLM platforms in San Juan, Puerto Rico. The role is hybrid, with an average of two days per week spent in an HPE office. It combines deep technical leadership in generative AI systems with mentoring and cross-team influence.

Key responsibilities

• Define technical strategy and multi-year product roadmaps, evaluate emerging technologies and drive customer-focused innovation
• Design production-grade LLM and agentic solution architectures, including prompt engineering, fine-tuning and model customization
• Evaluate LLMs, set guardrails, and ensure privacy, bias mitigation and safety
• Design scalable, low-latency, multi-tenant distributed systems and manage observability, SLOs, incident response, capacity and cost
• Lead technical direction, mentor engineers and contribute to cross-functional initiatives
• Drive agile delivery, rapid prototyping and productization

Required profile

• Advanced degree in Computer Science, Machine Learning, Artificial Intelligence or a related discipline
• 15+ years of relevant industry experience
• Bachelor's degree in Computer Science, Engineering, Mathematics or a related field, or equivalent practical experience
• Proven technical leadership at Staff, Principal, Architect or equivalent level, with architecture ownership of large-scale production systems
• Demonstrated mentoring and coaching skills

Required skills

• Strong hands-on Python and Go, with solid API, async processing, testing and software design knowledge
• Deep understanding of transformer-based LLMs, tokenization, embeddings, prompt engineering and inference behavior
• Experience with production generative AI systems (RAG, agents, tool calling, evaluation pipelines, safety mechanisms)
• AWS, Kubernetes, infrastructure as code, CI/CD, Amazon Bedrock, Amazon EMR, Apache Spark, Apache Flink, Amazon Aurora PostgreSQL, pgvector, Amazon EKS and Amazon S3
• AI/ML frameworks (Hugging Face Transformers, PyTorch) and orchestration (LangChain, LangGraph, LlamaIndex)
• MLOps and LLMOps, including experiment tracking, model registries, automated evaluation and controlled releases
• Network architecture, hybrid/multi-region connectivity and distributed systems design

What we offer

• Benefits supporting physical, financial and emotional wellbeing
• Programs for personal and professional development
• An inclusive workplace with flexibility to manage work and personal needs