Principal Engineer – Generative AI & LLM Platforms

Principal Engineer – Generative AI & LLM Platforms This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Family Definition: Designs, develops, troubleshoots and debugs software programs for software enhancements and new products. Develops software including operating systems, compilers, routers, networks, utilities, databases and Internet-related tools. Determines hardware compatibility and/or influences hardware design. Management Level Definition: Contributions have visible technical impact on a product or major subcomponent.  Applies in-depth professional knowledge and innovative ideas to solve complex problems. Visible contributions improve time-to-market, achieve cost reductions, or satisfy current and future unmet customer needs. Recognized internal authority on key technology area applying innovative principles and ideas. Provides technical leadership for significant project/program work. Leads or participates in cross-functional initiatives and contributes to mentorship and knowledge sharing across the organization.

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 Education and Experience Required: Advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline 15+ years of relevant industry experience Knowledge and Skills: Proven technical leadership at Staff, Principal, Architect, or equivalent level, with influence across multiple teams or product areas and experience in delivering significant ownership of architecture for large-scale production systems. Strong hands-on proficiency in Python and Golang; solid understanding of APIs, asynchronous processing, testing, and software design principles. Deep understanding of transformer-based LLMs, tokenization, embeddings, context management, prompt engineering, inference behavior, and common model failure modes. Experience building and operating production grade Generative AI systems, including RAG, agents or tool-calling workflows, evaluation pipelines, and safety mechanisms. Practical experience customizing models through fine-tuning or parameter-efficient techniques and measuring quality against representative datasets. Hands on experience with AWS and cloud-native architecture, including compute, storage, identity and access management, monitoring, and deployment automation; strong networking domain knowledge covering routing & switching protocols,  VPC design, private connectivity, network security, hybrid cloud connectivity, and troubleshooting of distributed application traffic flows. Expertise in distributed systems and systems design, including scalability, reliability, security, performance, data architecture, and cost optimization.