Director, Sales Engineering - Networking

Summary

The Director, Sales Engineering - AI Storage & Networking for the Federal sector serves as the primary technical resource for the Federal account management team. This role provides expert pre‑sales and post‑sales support for complex AI‑driven data center solutions within Government agencies. As the key technical advisor, you will drive the technology evaluation stage of the sales process through consultative assessments of mission‑critical requirements and deep‑dive product demonstrations.

You must be able to articulate the value of high‑performance storage and networking architectures to both senior leadership (SES/General Officers) and technical subject matter experts, ensuring complete customer satisfaction across the entire procurement lifecycle.

Remote Employee US, NH, US. This is a remote position requiring travel as necessary.

Demos & Presentations: Lead the development and delivery of high‑impact product demonstrations and technical presentations tailored to Federal use cases, including the design, configuration and management of on‑site PoC activities.

Field Representation: Represent AI storage and networking solutions at major Federal field events, such as MILCOM, AFCEA, or agency‑specific technology days.

Proposal Leadership: Lead technical responses for functional and technical elements of Federal RFIs, RFPs, and SOOs.

Voice of the Customer: Convey specific Federal requirements—including security, ruggedization, and performance needs—to internal Product Management and Technology teams.

Supply Chain

Collaboration:

Coordinate with 3rd party suppliers and Celestica Product Line Marketing to align technology implementation with Federal mandates.

Operational Travel: Ability to travel throughout the assigned Commercial and Federal territory and to manufacturing facilities as needed for customer engagements.

Storage Architecture Mastery: Deep experience with Storage systems (Traditional HA/Dual SP and Scale‑Out storage architectures) and associated network transport systems, topologies, and protocols directly in Storage environments (e.g., RoCE, NVMe‑oF, Ethernet) is a must. Experience with AI cluster optimization in relation to KV Cache and the role it plays in accelerating inference operations (prefill and decode) is very desirable.

Storage Proficiency: Experience with AI‑optimized storage architectures and related computer systems that rely on high‑speed networks.

Technical Environment: Experience with software defined storage operating systems such as VAST Data, Xinnor, Hammerspace, Weka, Qumulo. Proficiency with SONiC, Linux, and networking NOS technologies is highly desired.

Integration

Skills:

Familiarity with rack‑level integration, including high‑speed optical modules and advanced cabling for AI clusters.

Communication: Exceptional presentation and written communication skills for high‑stakes briefings in both Commercial and Federal segments.

Analytical Approach: Ability to solve complex sales obstacles through creative, adaptive, and analytical approaches.

• Duties of this position are performed in a normal office environment.
• Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data.
• Repetitive manual movements (e.g., data entry, using a computer mouse, etc.) are frequently required.
• Duties of this position may require working very long hours for months at a time.
• Up to 50% travel is possible.

• Experience:
  
  12 to 14 years of applicable technical experience, with at least 5+ years focused on AI storage, high‑performance computing (HPC), or datacenter networking sales.
• Federal Expertise:
  Proven track record selling into Federal Enterprise and/or Defense markets; understanding of Federal procurement cycles and security standards is required.

• Bachelor’s degree in Computer Science, Engineering, or related field is required.
• MBA or relevant Master's preferred.

The salary range described in this posting is an estimate by the Company, and may change based on several factors, including but…