Principal Engineer – Generative AI & LLM Platforms

Job Description:

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.

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

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.

• Demonstrated mentoring and coaching skills, with a track record of growing engineers, building technical communities, facilitating constructive design discussions, and leading through influence in ambiguous environments.

• Strong innovation mindset, intellectual curiosity, and ability to translate emerging technologies into practical solutions through rapid experimentation, evidence-based decisions, and thoughtful risk management.

• Demonstrated ability to work in agile delivery models, rapidly build and present functional proofs of concept, and use early technical validation to guide priorities, architecture decisions, and incremental delivery.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience

• Cloud, Platform, and Network Architecture:

• AWS cloud, Kubernetes, infrastructure as code, and CI/CD

• Amazon Bedrock and AWS AI/ML services

• Amazon EMR, Apache Spark, and Apache Flink

• Amazon Aurora PostgreSQL, pgvector, Amazon EKS, and Amazon S3

• Secure network architecture and hybrid/multi-region connectivity

• AI/ML Frameworks and Orchestration:

• Hugging Face Transformers and PyTorch

• LangChain, LangGraph, and LlamaIndex

• MLOps and LLMOps:

• Experiment tracking, model registries, and version management

• Automated model evaluation and controlled releases

• AI Platform Architecture and Inference:

• Multi-model platforms, AI gateways, and model routing

• Semantic caching and batch/streaming inference

• Security, and Compliance:

• Privacy-preserving AI and adversarial testing

• AI red teaming, content safety, and explainability

• AI regulatory compliance

• Thought Leadership:

• Patents, publications, open-source contributions, and technical thought leadership

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.

Job:

Job Level:

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

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