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 about 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, and handle prompt engineering, fine-tuning and model customization
• Evaluate LLMs, set guardrails, and address privacy, bias 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 influence cross-team work
• 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, EMR, Spark, Flink, Aurora PostgreSQL, pgvector, EKS and S3
• Frameworks such as Hugging Face Transformers, PyTorch, LangChain, LangGraph and LlamaIndex
• MLOps/LLMOps, model evaluation, automated releases, AI platform architecture and inference
• Network knowledge (routing, switching, VPC, hybrid cloud) and distributed systems expertise

What we offer

• Benefits supporting physical, financial and emotional wellbeing
• Programs for personal and professional development
• An inclusive workplace with flexible arrangements