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

Description

The role is the technical champion for the company's secure, localized object storage products. It joins machine learning innovation with high-performance data infrastructure, using hands-on demos, proofs-of-concept, reference architectures, benchmark workflows, and technical content.

The company is a global edge-to-cloud business that helps other companies connect, protect, and analyze their data and applications wherever they run, so they can act on what they learn.

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 knowledge of object storage, AI/ML pipelines, distributed systems, infrastructure design, performance tuning, and technical communication.

Responsibilities

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

Requirements

• A Bachelor's or Master's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
• Typically 10+ years of experience in technical marketing, systems engineering, storage engineering, infrastructure architecture, or a related technical field.
• Deep hands-on experience with S3 API object storage, including bucket policies, lifecycle management, object locking, and multi-tenant data isolation.
• A solid grasp of data lakehouse architectures and formats such as Apache Iceberg, Delta Lake, and Parquet.
• Practical experience designing or running distributed storage systems, covering 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 integration, developer tooling, or systems development.
• Proven success in technical writing, public speaking, technical video production, customer enablement, or explaining complex infrastructure to varied audiences.
• Understanding of AI data ingestion, data preparation, checkpointing, caching, and storage throughput needs.
• 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 such as InfiniBand, RoCE/RDMA, and Ethernet from 100GbE to 400GbE or faster.
• Experience with Docker, Kubernetes, and storage integrations through the Container Storage Interface (CSI).
• Expertise in benchmarking and load testing with tools such as fio, warp, mdtest, or custom workload generators.
• The ability to analyze performance data and clearly explain storage behavior, scalability, and optimization options.
• Strong collaboration, mentoring, presentation, technical writing, and stakeholder management skills.
• The ability to turn complex infrastructure and AI/ML concepts into clear technical stories, proven solutions, and practical customer guidance.

Conditions

This is a hybrid role that requires working from an office about 2 days per week on average.

The role is based in the United States and sits in the Engineering function at job level TCP05.

Annual base salary is USD 178,000 to 339,000 in Massachusetts and USD 157,000 to 361,000 in North Carolina and Texas. Variable incentives may also be offered, and the final offer may vary by location, experience, education, training, or skill level.

The company is an equal opportunity employer and complies with laws on the use of arrest and conviction records in hiring.

Benefits

• Comprehensive health and wellbeing benefits covering physical, financial, and emotional wellness.
• Development programs for career goals, such as becoming a recognized expert in your field or moving into another division.
• Flexibility to manage work and personal needs.