Job Overview
Location
Remote - United States
Job Type
Full-time
Category
Engineering
Date Posted
July 9, 2026
Full Job Description
đź“‹ Description
- • Lead the engineering team responsible for the day-to-day implementation, scaling, and operation of AI compute clusters.
- • Translate engineering roadmaps and technical requirements from the Director of AI Infrastructure into detailed project plans and execution milestones.
- • Drive delivery of cluster deployments, hardware bring-up, node configuration, and integration with orchestration and scheduling systems.
- • Ensure cluster reliability, uptime, and performance through monitoring, automation, and continuous operational improvements.
- • Oversee lifecycle operations for bare metal and GPU fleets, including provisioning, configuration management, firmware/driver updates, and hardware validation.
- • Manage incident response for GPU and cluster infrastructure, ensuring timely resolution and root-cause analysis.
- • Work closely with AI/ML, SRE, Networking, and Hardware Engineering teams to ensure cluster capabilities meet training and inference needs.
- • Coordinate with Product to confirm technical requirements, feature readiness, and delivery timelines.
- • Support integrations across networking, storage, scheduler, and resource orchestration components.
- • Improve tooling and automation for cluster provisioning, observability, configuration management, and large-scale fleet operations.
- • Contribute to the development and refinement of multi-tenant scheduling, workload management, and orchestration systems in partnership with senior technical staff.
- • Identify performance bottlenecks and propose engineering-level optimizations.
- • Coach and mentor engineers, fostering a high-performance, detail-oriented engineering culture.
- • Support career development, expectations, and performance management for team members.
- • Help refine engineering processes, including code reviews, testing standards, documentation, and operational runbooks.
🎯 Requirements
- • 6–10 years of experience in infrastructure engineering, HPC, large-scale systems, or similar fields.
- • Strong understanding of AI compute infrastructure, including GPU/CPU clusters, distributed training architectures, and high-performance networking (InfiniBand/RDMA).
- • Experience running production bare metal, GPU, or hardware fleet operations at meaningful scale.
- • Hands-on expertise with Linux systems, Kubernetes or Slurm, provisioning tools (Terraform, Ansible), observability platforms, and networking fundamentals.
- • Proven track record in cluster operations, hardware bring-up, distributed systems, or ML workload support.
- • Experience leading engineering teams or pods, with the ability to manage execution while staying close to technical work.
- • Ability to communicate effectively with cross-functional engineering teams and translate strategy into actionable engineering tasks.
- • Strong execution mindset with the ability to prioritize, deliver, and adapt in a fast-paced environment.
🏖️ Benefits
- • Excellent Medical Benefits w/ 100% company-paid premiums for employee only plan + 100% company-paid dental & vision premiums.
- • 401(k) plan that matches 100% up to 4% with immediate vesting.
- • Professional Development Reimbursement of $2,500 each year.
- • 11 Holidays + Paid Time Off Accrual + Rollover Plan + take your birthday off.
- • Commitment matters to Vultr! Increased PTO at 3 year & 10 year anniversary + 1 month paid sabbatical every 5 years + Anniversary Bonus each year.
- • $500 first year remote office setup + $400 each following year for new equipment.
- • Internet reimbursement up to $75 per month.
- • Gym membership reimbursement up to $50 per month.
- • Company-paid Wellable subscription.
Skills & Technologies
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About The Constant Company, LLC
The Constant Company, LLC operates the Vultr cloud infrastructure brand, providing on-demand compute, storage, bare-metal, and managed Kubernetes services from 32 global data centers. Founded in 2014, the company targets developers, SaaS businesses, and enterprises with hourly billing, API-driven provisioning, and standardized hardware. Services include virtual machines, block storage, load balancers, object storage, managed databases, and cloud GPUs, all accessible through a unified control panel and REST API. Vultr emphasizes price-performance, global reach, and rapid deployment for web applications, CI/CD workflows, and edge workloads without long-term contracts.
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