Technical Marketing Engineer (TME) for AI & On-Premises Object Storage

Hewlett Packard Enterprise • Durham, NC

1d • $157,000 - $361,000 • Hybrid

About The Position

The Technical Marketing Engineer for AI and on-premises object storage serves as the technical champion for HPE’s secure, localized object storage solutions. The role bridges machine learning innovation and high-performance data infrastructure by creating hands-on demonstrations, proofs of concept, reference architectures, benchmark workflows, and technical content.

The engineer works with enterprise architects, data scientists, infrastructure engineers, Solutions Architects, Sales Engineers, channel partners, Product Management, and Storage Engineering. The position calls for expertise in object storage, AI/ML pipelines, distributed systems, infrastructure design, performance optimization, and technical communication. It is hybrid, with an average requirement of two days per week working from an HPE office.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline, or equivalent practical experience.
• Typically 10+ years of experience in technical marketing, systems engineering, storage engineering, infrastructure architecture, or a related technical field.
• Deep experience with S3 API-based object storage, including bucket policies, lifecycle management, object locking, and multi-tenant data isolation.
• Strong understanding of data lakehouse architectures and formats such as Apache Iceberg, Delta Lake, and Parquet.
• Practical experience designing or operating distributed storage systems, including erasure coding, replication, metadata management, and cluster scaling.
• Experience with AI/ML training workflows and frameworks such as PyTorch, TensorFlow, Ray, or Hugging Face Transformers.
• Proficiency in Python or Go for infrastructure automation, API integrations, developer tooling, or systems development.
• Demonstrated success in technical writing, public speaking, technical video creation, customer enablement, or translating complex infrastructure topics for diverse audiences.
• Strong understanding of AI data ingestion, data preparation, checkpointing, caching, and storage throughput requirements.
• Knowledge of enterprise hardware sizing, including node density, CPU and RAM configurations, NVMe flash tiers, GPU clusters, and storage fabrics.
• Familiarity with high-speed networking technologies, including InfiniBand, RoCE/RDMA, and 100GbE to 400GbE or higher Ethernet environments.
• Experience with Docker, Kubernetes, and storage integrations using the Container Storage Interface (CSI).
• Expertise in benchmarking and load testing with tools such as fio, warp, mdtest, or custom workload generators.
• Ability to analyze performance data and communicate storage behavior, scalability, and optimization opportunities clearly.
• Excellent collaboration, mentoring, presentation, technical writing, and stakeholder management skills.
• Ability to translate complex infrastructure and AI/ML concepts into compelling technical narratives, validated solutions, and practical customer guidance.

Responsibilities

• Design, build, and maintain demonstration environments, infrastructure blueprints, hardware sizing guides, and validated reference architectures combining on-premises object storage with AI compute infrastructure.
• Develop AI/ML benchmark workflows, proofs of concept, and Jupyter notebooks demonstrating performance optimization for data preparation, ingestion, checkpointing, and large-scale unstructured data processing.
• Create technical whitepapers, deployment guides, solution briefs, competitive analyses, technical videos, and other content explaining storage performance, scalability, and AI infrastructure design.
• Deliver technical enablement for internal Solutions Architects, Sales Engineers, channel partners, and customers addressing complex on-premises infrastructure requirements and objections.
• Evaluate storage I/O behavior, bottlenecks, scaling limitations, and workload performance using industry-standard benchmarking tools and custom load generators.
• Provide field-driven technical feedback to Product Management and Storage Engineering on customer requirements, product capabilities, scale limitations, and performance opportunities.
• Mentor less-experienced engineers and contribute to software systems design, infrastructure automation, and technical innovation.

Benefits

• Comprehensive benefits intended to support physical, financial, and emotional wellbeing.
• Career development programs to help employees pursue career goals, deepen expertise, or apply their skills in another division.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior