Upscale AI
Principal Solutions Engineer
US - Headquarters · Principal
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About the role
- We focus on first-principles engineering across silicon, systems, and networking-where performance, scale, and execution are critical.
- Our team is talent-dense and high-performing.
- If you're looking to do high-impact work, move fast, and help define the infrastructure behind the future of AI-Upscale is where you can produce meaningful work at the frontier-and operate at a high standard.
Responsibilities
- Manage high-value global customer accounts in partnership with the Account Manager.
- Drive complex, full-cycle solution sales from ASIC-level to system-level and rack-scale deployments.
- Design and propose solutions leveraging Upscale's product portfolio.
- Lead technical discovery, gather customer requirements, and develop proof-of-concept validation and demos to demonstrate product and solution capabilities across AI clusters - GPU, NIC, xPU, and switch tray platforms.
- Deliver compelling technical presentations, product demonstrations, and feature deep-dives to customer stakeholders.
- Identify and develop new business opportunities within both existing and prospective accounts.
- Collaborate with Sales and Product teams to respond to RFPs, RFIs, RFQs, and other sales proposals with tailored technical input on ASIC, scale-up interconnect, and networking architecture.
- Partner cross-functionally with engineering, product management, and operations teams to deliver on customer requirements and align product roadmaps with market needs, including emerging standards such as ESUN, SUE, ETH, IP and UALink.
Requirements
- Minimum of 10 years of pre-sales experience as a Sales Engineer, Solutions Engineer, or Solutions Architect in the AI infrastructure, semiconductor, or networking sector.
- Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, or a related engineering discipline, or equivalent industry experience.
- Hands-on experience with scale-up networking and interconnect technologies as well as scale-out data center and WAN networking.
- Working knowledge of major network operating systems such as SONiC, Arista EOS, Juniper Junos, Cisco IOS, etc.
- Familiarity with emerging scale-up and interconnect standards, including ESUN, UALink (UAL), and SUE.
- Excellent communication, presentation, and interpersonal skills, with the ability to effectively engage with technical and executive stakeholders.
- Willingness and ability to travel up to 25%, including international travel.
Skills
- Why join Upscale, Inc.
Compensation
- $239k-$266k
Company info
- We value ownership, technical rigor, and speed, and we offer the opportunity to work on foundational problems with immediate, real-world impact.
- You will work closely with customers to architect solutions that align with their business and technical goals, while representing their feedback internally to shape our product roadmap.
- This is an opportunity to make a significant impact in a fast-paced, high-growth environment, with exposure to strategic customers, emerging technologies, and industry-shaping innovations.
- Serve as a trusted technical advisor to customers, drawing on chip, board, and system-level expertise to guide them through solution design, evaluation, and adoption.
Equal opportunity
- Upscale, Inc., is building a team that reflects a wide range of perspectives, backgrounds, and experiences. We're proud to be an Equal Opportunity Employer and consider all qualified applicants regardless of race, color, religion, national origin, sex, sexual orientation, gender identity, disability, or veteran status.
- Accessibility & Accommodations
- We're committed to making our hiring process accessible to everyone. If you need accommodations at any stage, just reach out to us at hiring@upscaleai.com -we're happy to help. Note: This inbox is only for accommodation requests.
- Upscale, Inc., is building a team that reflects a wide range of perspectives, backgrounds, and experiences.
This listing is sourced directly from Upscale AI's careers page and normalized into a canonical job model.