Technical Support Engineer – Inference

Together AI

Technical Support Engineer maintaining Together AI’s GPU-based inference infrastructure and customer endpoints. Resolving complex AI service incidents while supporting Kubernetes, observability, and infrastructure-as-code operations on US weekend shifts.

Posted 8/4/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $160,000 - $230,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing GPU clusters and AI services, with strong capabilities in Kubernetes, Infrastructure as Code, and complex problem-solving. Proficient in customer communication and cross-functional collaboration to ensure system health and performance.

Highest-signal resume keywords

Kubernetes ManagementAI and ML TechnologiesInfrastructure as CodePython and TypeScript ProgrammingPrometheus and Grafana Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

KubernetesPythonTypeScriptAnsibleSLURMGPU TechnologiesHPC EnvironmentsREST API DebuggingInfrastructure as CodeLLM Inference Frameworks

Soft Skills

Excellent CommunicationComplex Problem-SolvingInterpersonal SkillsProject ManagementCross-Functional Collaboration

Tools & Technologies

AWSGCPAzureVast StorageWeka StorageNFS StorageHigh-Performance Network FabricsCurlPostmanGrafana

Industry Keywords

SREDevOpsAI ServicesGPU Cluster ManagementCompute-Cluster AdministrationTechnical SupportIncident ManagementSystem Health MonitoringTraffic RoutingDocumentation

Tech Stack

Tools & technologies

AnsibleAWSAzureGoogle Cloud PlatformGrafanaJavaScriptKubernetesNFSPrometheusPythonSwitchingTypeScript

About the role

Key responsibilities & impact

Engage directly with customers to resolve complex technical challenges involving GPU clusters, inference, and fine-tuning services
Act as a customer-facing SRE to keep customer inference endpoints on Kubernetes healthy, stable, and performant
Become a product expert and serve as the last technical defense before escalation to Engineering and Product
Assist with hardware and platform migrations by validating system health and traffic routing
Monitor dashboards, detect anomalies, and escalate with data-backed analysis
Manage customer communications during incidents and degradations
Translate technical findings into clear, evidence-backed customer updates
Execute infrastructure changes through pull requests and infrastructure-as-code for endpoint configuration, model deployment, capacity scaling, and cluster configuration
Flag engine-level bugs with logs and reproduction steps
Collaborate with Engineering, Research, Product, Sales, Support, and senior leaders to address customer concerns
Identify support-case patterns and help drive Together AI’s product roadmap
Maintain documentation covering system configurations, procedures, troubleshooting guides, and FAQs
Provide support coverage during holidays, nights, and weekends as required

Requirements

What you’ll need

6+ years of experience in a customer-facing technical role, SRE, DevOps, or infrastructure engineering, including at least 1 year supporting an AI service
Experience as an SRE or DevOps engineer working with Kubernetes
Strong knowledge of AI, ML, GPU technologies, and HPC environments
Production-level experience with Kubernetes, SLURM, Ansible, high-performance network fabrics, NFS storage, and container infrastructure
Familiarity with Vast and Weka storage systems in HPC environments
Ability to diagnose complex network-layer issues and read traces
Strong knowledge of Python, TypeScript, and/or JavaScript, with curl and Postman-like testing/debugging experience
Expertise with Prometheus and Grafana at scale
Deep familiarity with REST API debugging and HTTP semantics
Experience with LLM inference frameworks, LoRA fine-tuning, and common training failure modes
Experience with Infrastructure as Code and Git-based workflows
Background in GPU cluster management
Experience with AWS, GCP, and/or Azure
Understanding of compute-cluster installation, configuration, administration, troubleshooting, and security
Complex technical problem-solving and troubleshooting ability
Ability to work cross-functionally with Sales, Engineering, Support, Product, and Research
Strong ownership and willingness to learn
Excellent communication and interpersonal skills, including explaining complex technical concepts to non-technical stakeholders
Ability to manage multiple projects, context switching, and prioritization
Ability to work US daytime hours, including Saturday and Sunday plus two additional weekdays
Ability to work a four-day, ten-hour shift with additional weekend on-call coverage
Flexibility to provide holiday, night, and weekend support

Benefits

Comp & perks

Startup equity
Health insurance
Other benefits
Flexibility in terms of remote work
Competitive compensation