Technical Compute Qualification Manager

Together AI is growing its compute footprint, and making sure new capacity meets our technical standards is an important priority for the company. Every new cluster has to clear a technical bar before it carries customer workloads, and this role owns that bar. As Technical Compute Qualification Manager, you will run the process that screens and qualifies prospective compute providers, taking each prospective  deployment through a structured evaluation across compute, networking, storage, power, cooling, and operations.

You will coordinate various engineering partners through validation, review provider specifications and test results, and produce clear go/no-go recommendations on whether new capacity meets our standards. It is a high-impact, process-driven role for someone technical enough to know when a spec sheet does not add up, and additional diligence needs to be completed, and organized enough to drive many evaluations to closure in parallel. "You will deep-dive into critical hardware performance metrics, proactively identifying potential bottlenecks in cluster architecture before they impact our end customers training or inference workloads." Conduct diligence and work with engineering teams to make assessments regarding technical and operational resilience.

• →Own and continuously improve the end-to-end qualification process for new compute capacity, from initial provider intake through final go/no-go recommendation.
• →Run multiple provider evaluations in parallel, setting timelines, tracking status, and keeping every stakeholder aligned on what is needed and by when.
• →Partner with infrastructure engineering, network engineering, data center engineering, and SRE teams to plan and coordinate technical validation, then translate their findings into clear decisions for leadership.
• →Review provider technical specifications and questionnaire responses for completeness and accuracy, flagging gaps, inconsistencies, and risks that warrant follow-up.
• →Conduct first-pass analysis of provider data yourself: compare specifications across suppliers , sanity-check performance claims, and surface issues before deeper engineering review.
• →Maintain the standards, templates, and documentation that define what meets spec across compute, networking, storage, power, cooling, and operational support.
• →Build a structured, auditable record of evaluation outcomes that informs sourcing decisions and scales the qualification function as the team grows.

• 5+ years in technical program or project management, infrastructure program management, or a comparable technical operations role, ideally involving hardware, data center, or large-scale compute environments.
• Proven ability to run multiple complex, cross-functional workstreams to deadline, with strong organization and stakeholder management.
• Working technical fluency across data center infrastructure: server and GPU hardware, high-performance networking (InfiniBand or Ethernet fabrics), storage, and power and cooling fundamentals; enough depth to read a detailed technical specification and know what to question.
• Hands-on comfort with data: able to write scripts or queries (for example, Python or SQL) to compare, validate, and analyze provider specifications and test results independently.
• Excellent written and verbal communication; able to turn dense technical detail into clear recommendations for both engineers and executives.
• Willingness to travel to provider and data center sites as needed.
• This is not an engineering manager role

• Experience qualifying, commissioning, or accepting GPU clusters or HPC infrastructure against defined performance and reliability standards.
• Familiarity with AI training and inference infrastructure, including interconnect topologies, cluster bring-up, and acceptance testing.
• Experience in AI/HPC cluster design.
• Background working directly with hardware vendors, colocation providers, or cloud capacity providers.

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our Privacy Policy at https://www.together.ai/privacy