Technical Account Manager

DDN; Santa Clara (CA); In loco; USD 150.000 - 210.000; Tempo pieno

Descrizione del lavoro

DDN is seeking a Technical Account Manager (TAM) to lead hands-on deployment, integration, and optimization of DDN storage and data management systems for enterprise and AI/ML customers. You will bridge Engineering with customer Site Reliability teams to ensure performance, reliability, and scalability across distributed HPC/AI workloads.

You will automate deployments, document procedures, and collaborate with Sales and Product teams to translate field requirements into product enhancements.

Competenze

• 8+ years hands-on 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.

Mansioni

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

Conoscenze

Linux administration

Large-scale HPC/AI infrastructure

Parallel file systems

Networking (InfiniBand & high-Perf IP)

DevOps scripting (Python, Bash, Anible

Containers & orchestration (Kubernetes

Technical documentation & runbooks

Effective communication with execs &研发

Willingness to travel

Hardware handling (lift 75 lbs)

Strumenti

Prometheus

Grafana

ELK stack

Kubernetes

Slurm

Ansible

Descrizione del lavoro

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.