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

Description

The company builds edge-to-cloud technology that lets customers link, secure, examine and act on their data and apps wherever it sits.

This role is the technical voice for the team's secure, localized object storage. You will combine machine learning work with high-performance data infrastructure through demos, proof-of-concepts, reference architectures, benchmark workflows and technical content.

You will work with enterprise architects, data scientists, infrastructure engineers, Solutions Architects, Sales Engineers, channel partners, Product Management and Storage Engineering. The role calls for deep skill in object storage, AI and ML pipelines, distributed systems, infrastructure design, performance tuning and technical communication.

Responsibilities

• Build and maintain demo environments, infrastructure blueprints, hardware sizing guides and validated reference architectures that pair on-premises object storage with AI compute.
• Write AI and ML benchmark workflows, proofs-of-concept and Jupyter notebooks that show how to optimize data preparation, ingestion, checkpointing and large-scale unstructured data processing.
• Produce whitepapers, deployment guides, solution briefs, competitive analyses, technical videos and other material on storage performance, scalability and AI infrastructure design.
• Enable internal Solutions Architects, Sales Engineers, channel partners and customers on complex on-premises requirements, including how to handle objections.
• Assess storage I/O behavior, bottlenecks, scaling limits and workload performance using standard benchmarking tools and custom load generators.
• Send field-based technical feedback to Product Management and Storage Engineering on customer needs, product capabilities, scale limits and performance gaps.
• Mentor less experienced engineers and contribute to software design, infrastructure automation and new technical ideas.

Requirements

• Hold a bachelor's or master's degree in computer science, information systems or a related discipline, or have equivalent hands-on experience.
• Typically have 10+ years in technical marketing, systems engineering, storage engineering, infrastructure architecture or a closely related technical field.
• Have deep experience with S3 API object storage, including bucket policies, lifecycle management, object locking and multi-tenant data isolation.
• Understand data lakehouse architectures and formats such as Apache Iceberg, Delta Lake and Parquet.
• Have worked with distributed storage systems, covering erasure coding, replication, metadata management and cluster scaling.
• Have experience with AI and ML training workflows and frameworks such as PyTorch, TensorFlow, Ray or Hugging Face Transformers.
• Be proficient in Python or Go for infrastructure automation, API integration, developer tooling or systems development.
• Have a track record in technical writing, public speaking, technical video, customer enablement or explaining complex infrastructure to varied audiences.
• Understand AI data ingestion, data preparation, checkpointing, caching and storage throughput needs.
• Know enterprise hardware sizing, including node density, CPU and RAM configurations, NVMe flash tiers, GPU clusters and storage fabrics.
• Be familiar with high-speed networking such as InfiniBand, RoCE/RDMA and 100GbE to 400GbE or faster Ethernet.
• Have experience with Docker, Kubernetes and storage integrations through the Container Storage Interface (CSI).
• Be skilled at benchmarking and load testing with tools such as fio, warp, mdtest or custom workload generators.
• Analyze performance data and explain storage behavior, scalability and optimization options clearly.
• Collaborate well, mentor others, present, write and manage stakeholders effectively.
• Turn complex infrastructure and AI/ML concepts into clear technical narratives, validated solutions and practical customer guidance.

Conditions

Hybrid role with an average of 2 days per week in a company office.

Based in the United States, job level TCP05 in Engineering.

Base salary is USD 178,000 to 339,000 in Massachusetts and USD 157,000 to 361,000 in North Carolina and Texas.

Final pay may differ based on location, experience, education or training, and skill level. Variable incentives may also be offered on top of base salary.

The company is an equal opportunity employer that welcomes applicants with disabilities, provides accommodations on request and follows laws on employer use of arrest and conviction records.

Benefits

• Health and wellbeing coverage designed to support physical, financial and emotional wellbeing, with US benefit details published online.
• Development programs to help you reach career goals, from becoming a subject expert in your field to moving into another division.