Software Engineer, Infrastructure

Tavus

$120K — $150K *
US-AnywhereRemote in San Francisco, CA
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Hands-on GPU inference experience in deploying and optimizing workloads.
  • Extensive knowledge of Kubernetes and EKS for routing and scheduling.
  • Deep experience with AWS services for creating repeatable processes.
  • A proven history of taking ownership and setting technical direction.
  • Ability to clearly explain complex ideas to both technical and non-technical audiences.

Responsibilities

  • Own the systems behind CVI's inference deployments, managing GPU infrastructure for live conversations.
  • Expand the GPU footprint by integrating new providers and setting up clusters on EKS.
  • Enhance uptime by contributing to security and SOC2 compliance efforts.
  • Identify and rectify issues proactively within the infrastructure and deployment pipeline.
  • Optimize GPU load times and responsiveness in real-time contexts.

Benefits

  • Work in a cutting-edge, dynamic environment focused on real-time systems.
  • Join a growing team of infrastructure experts tackling innovative challenges.
  • Opportunities for continuous learning and hands-on problem solving.
  • Contribute to the design and implementation of scalable infrastructure.
Full Job Description
The Role

We're hiring a Senior Software Engineer (Infrastructure) to own the systems behind CVI, our real-time conversational product. Every live conversation between a person and a PAL runs on infrastructure your team owns. You'll take goals like uptime, latency, and cost and chase them wherever they lead, including into backend services and product code.

What you'll own
  • CVI's inference deployments. The GPU infrastructure serving live conversations across multiple providers and regions. You'll join as an early senior member of a growing infra team, working on projects like tuning the newest GPU generations and cutting cold-start and model load times so users wait less.
  • Expanding our GPU footprint. You'll bring on new providers and regions, stand up clusters on EKS, and build the routing, scheduling, and throughput needed for fast weight loading.
  • Uptime. You'll be one of the people pushing our uptime bar higher, along with the security and SOC2 work that keeps our infrastructure trustworthy.
  • Fix what you find. When you see a problem, you have the trust and the mandate to fix it or flag it. Reworking our deploy pipeline so shipping is fast and boring is exactly the kind of thing you'd take on.
What this role has shipped
  • Multi-provider, multi-region inference infrastructure: routes live conversations across GPU providers and regions, so one provider's outage never becomes a user's problem
  • CUDA optimizations for Phoenix, our video rendering model: doubled the frame rate by tracing and optimizing hot paths with our researchers
  • Parallel conversations on a single GPU: several live conversations sharing one card, multiplying what the fleet can serve
Who you are
  • You own outcomes. You don't stop where "infrastructure" ends. If the fix lives in backend code or the CVI stack, you dive in, and you don't wait for a ticket to do it.
  • You're energized by unfamiliar problems. If the next thing that matters is standing up a training deployment you've never touched, you jump in and learn on the fly.
  • You adapt as priorities evolve. In a space moving this fast, the most important thing to build can change as we learn. When it does, you adjust course without losing momentum.
  • You care about this problem. Keeping large-scale, real-time systems fast and reliable is something you think about unprompted.
Requirements
  • Hands-on GPU inference experience. You've deployed and optimized inference workloads on GPUs and know what it takes to build reliable systems on top of GPU cloud providers.
  • Kubernetes and EKS depth, including routing and scheduling. You're comfortable designing how work gets placed across a fleet, and writing the services that make it happen.
  • Deep AWS experience. You're at home spinning up new services and turning them into simple, repeatable processes others can build on.
  • A senior track record of ownership. You've set technical direction, made decisions others built on, and carried ambiguous work over the finish line. You explain complex ideas clearly, to engineers and non-engineers alike.
Nice to have
  • Experience with GCP
  • Experience with video streaming infrastructure
  • Experience with training infrastructure or LLM serving
  • Experience with SOC2 or security compliance


If you don't check every box but this sounds like the work you want to be doing, apply anyway.

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