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Salary
$128k – $154k per year
Location
Hybrid (Santa Clara, United States)
Seniority
Staff · 8+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 23, 2026. DDN scores A on the Alion truth index.

Overview
Company
Impact
Profile match

DDN

DDN (DataDirect Networks) is a data storage company headquartered in Chatsworth, California that builds high-performance storage systems and a data intelligence platform for AI factories, cloud providers and supercomputing. Formed in 1998 through the merger of MegaDrive and ImpactData by co-founders Alex Bouzari and Paul Bloch, it has systems in 48 of the world's top 100 supercomputers and took a $300 million investment from Blackstone at a $5 billion valuation. It hires Rust, Go and Lustre software engineers, DevOps and build engineers, solutions architects, support engineers, manufacturing test technicians, and sales, tax and legal staff.

Overview

DDN is seeking a Technical Account Manager (TAM) to work directly with strategic enterprise and AI/ML customers, deploying, integrating, and optimizing DDN systems in production environments.

As an TAM, you will serve as the hands-on technical lead responsible for ensuring the success, reliability, and performance of large-scale, globally distributed HPC and AI infrastructure. You’ll act as the bridge between DDN Engineering and customer Site Reliability/Operations teams, translating complex requirements into tested, automated, and maintainable solutions. You will also collaborate with sales and sales engineering teams to develop and optimize offerings to ensure customer success.

Key Responsibilities

  • Deploy, configure, and optimize DDN storage and data management systems in customer environments.

  • Partner with customer Site Reliability Engineering (SRE) and Operations teams to ensure production performance, availability, and scalability.

  • Partner with DDN Sales and Sales Engineering teams to deliver solutions that add value to our customer environments

  • Automate system monitoring, deployment, and configuration tasks using scripts and DevOps tooling.

  • Troubleshoot and resolve complex issues across compute, storage, and networking layers.

  • Develop and maintain deployment documentation, procedures, and best practices.

  • Work with DDN Engineering and Product Management to translate field requirements into product enhancements (RFEs).

  • Act as the on-site technical focal point during deployments, upgrades, and critical incidents.

  • Lead technical meetings and operational reviews with customer and DDN stakeholders.

  • Drive continuous improvement through feedback loops with Product, Support, and Engineering teams.

  • Ensure alignment between deployed configurations and customer strategic roadmaps for HPC, AI, and ML workloads.

Required Skills and Experience

  • 8+ years of hands-on technical experience in systems engineering, deployment, or operations.

  • Strong Linux administration background.

  • Proven experience deploying and managing large-scale HPC, AI, or ML infrastructure.

  • Deep knowledge of parallel file systems (Exascaler, Lustre, or GPFS).

  • Experience configuring and troubleshooting InfiniBand and high-performance Ethernet networks.

  • Proficiency with DevOps tools and scripting (Python, Bash, Ansible, etc.) for automation and monitoring.

  • Familiarity with containers, orchestration (Kubernetes, Slurm), and hybrid/cloud environments.

  • Experience developing and maintaining technical documentation and operational runbooks.

  • Strong communication skills with the ability to interface directly with customer, engineering and executive teams.

  • Comfortable working independently in globally distributed environments.

  • Willingness to travel as required (up to 25%).

  • Ability to lift up to 75 pounds when supporting hardware installations.

Preferred Qualifications

  • Experience with AI/ML workflows, GPU-accelerated computing, or large-scale data pipelines.

  • Familiarity with observability stacks (Prometheus, Grafana, ELK).

  • Understanding of CI/CD and infrastructure-as-code methodologies.

  • Project management or DevOps certification (e.g., PMP, CKA, AWS Solutions Architect) is a plus.

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