Customer Success Engineer (CSE), GPU Cluster
Together AI · Not provided by source
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Job details
- Work model
- Not provided by source
- Salary
- Conflicting source ranges
- Location
- San Francisco
What the role asks for
What you'd do
- Serve as the named technical point of contact for a dedicated strategic customer, owning the end-to-end technical relationship across compute, networking, storage, and facilities
- Drive structured engagement through regular cadences - status reporting, technical steering meetings, quarterly business reviews (QBRs), and executive business reviews (EBRs) - spanning both operational and strategic levels
- Translate customer operational feedback into actionable input for Engineering, Product, and Infrastructure roadmaps
- Lead issue lifecycle management, escalation, and RCA authorship across all infrastructure domains in partnership with Support, SRE, DC Ops, and Engineering teams
- Own end-to-end RMA coordination and hardware lifecycle management, including acceptance testing, spare inventory management, and hardware health reporting for large-scale GPU deployments
- Maintain deep technical expertise across the customer's infrastructure stack - GPU compute, high-speed fabric, and large-scale storage systems - advising on configuration, operational best practices, and incident resolution
- Own the observability strategy for the customer estate, including alert policy definition, dashboard development, and proactive health management across all infrastructure layers
- Coordinate DC operations and facilities events in partnership with internal teams and hosting providers, ensuring SLA compliance and cluster availability
- Act as project manager for all capacity expansions, owning the full node deployment lifecycle from freight receipt through production acceptance
What they're asking for
- 5+ years in a customer-facing technical role, with 2+ years in dedicated technical account management or solutions architecture for large-scale AI or HPC infrastructureExperience
- Deep expertise in GPU infrastructure - GPU health diagnostics, RMA workflows, and hardware acceptance testingSkill
- Hands-on experience with large-scale Ethernet and InfiniBand fabric architectureSkill
- Working knowledge of enterprise storage systems, including high-density NVMe, parallel file systems, and metadata infrastructureSkill
- Experience with DC operations, facilities coordination, and hosting provider SLA managementSkill
- Strong ownership mindset for incident management, RCA authorship, and executive-level customer communicationSkill
- Proficiency in infrastructure monitoring and observability tooling (Prometheus, Grafana, or equivalent)Skill
- Proven ability to manage multiple concurrent workstreams with hyperscaler-level rigor and communication standardsSkill
- Proficiency in Python, Bash, or infrastructure automation tools preferredSkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
About the role As a Customer Success Engineer at Together AI, you will serve as the named technical owner for one of our most strategic customer relationships. You will be the primary technical point of contact across all infrastructure domains - compute, networking, storage, and facilities - ensuring flawless delivery and operational health of large-scale GPU deployments. This role sits at the intersection of deep infrastructure expertise and high-stakes customer partnership, making you a critical driver of both customer success and company growth. Responsibilities • Serve as the named technical point of contact for a dedicated strategic customer, owning the end-to-end technical relationship across compute, networking, storage, and facilities • Drive structured engagement through regular cadences - status reporting, technical steering meetings, quarterly business reviews (QBRs), and executive business reviews (EBRs) - spanning both operational and strategic levels • Translate customer operational feedback into actionable input for Engineering, Product, and Infrastructure roadmaps • Lead issue lifecycle management, escalation, and RCA authorship across all infrastructure domains in partnership with Support, SRE, DC Ops, and Engineering teams • Own end-to-end RMA coordination and hardware lifecycle management, including acceptance testing, spare inventory management, and hardware health reporting for large-scale GPU deployments • Maintain deep technical expertise across the customer's infrastructure stack - GPU compute, high-speed fabric, and large-scale storage systems - advising on configuration, operational best practices, and incident resolution • Own the observability strategy for the customer estate, including alert policy definition, dashboard development, and proactive health management across all infrastructure layers • Coordinate DC operations and facilities events in partnership with internal teams and hosting providers, ensuring SLA compliance and cluster availability • Act as project manager for all capacity expansions, owning the full node deployment lifecycle from freight receipt through production acceptance Qualifications • 5+ years in a customer-facing technical role, with 2+ years in dedicated technical account management or solutions architecture for large-scale AI or HPC infrastructure • Deep expertise in GPU infrastructure - GPU health diagnostics, RMA workflows, and hardware acceptance testing • Hands-on experience with large-scale Ethernet and InfiniBand fabric architecture • Working knowledge of enterprise storage systems, including high-density NVMe, parallel file systems, and metadata infrastructure • Experience with DC operations, facilities coordination, and hosting provider SLA management • Strong ownership mindset for incident management, RCA authorship, and executive-level customer communication • Proficiency in infrastructure monitoring and observability tooling (Prometheus, Grafana, or equivalent) • Proven ability to manage multiple concurrent workstreams with hyperscaler-level rigor and communication standards • Proficiency in Python, Bash, or infrastructure automation tools preferred About Together AI 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. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $260-290K OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Location San Francisco, CA (Hybrid) or New York, NY (Hybrid) Equal Opportunity 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
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