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Software Engineer, Infrastructure

Join Tavus as a Senior Software Engineer to enhance the infrastructure behind real-time AI conversations.

Location
Remote
Compensation
Not disclosed
Level
senior
Type
full time

Posted by employer 4 months ago

First seen on Joblaze 1 week ago

Last verified on the company career page 1 day ago

Apply at Tavus → Save job Scanned from tavus.io

Skills & Technologies

AI in the day-to-day

Our real-time human simulation models let machines see, hear, respond, and even look real.

Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.

Joblaze summary

In this role, the Senior Software Engineer for Infrastructure at Tavus will manage the systems that support real-time conversations in their AI-driven product. Key responsibilities include optimizing GPU infrastructure, enhancing uptime, and streamlining deployment processes to ensure reliability and efficiency. This position is ideal for a seasoned engineer with a strong background in GPU inference, Kubernetes, and AWS, who thrives in dynamic environments and is eager to tackle complex challenges. Tavus, a Series B company, is focused on pioneering human-computer interaction, making this an exciting opportunity to contribute to innovative technology.

Joblaze insights

Quick facts

What's the tech stack?
Joblaze extracted these technologies from the posting: AWS, CUDA, EKS, GPU, Kubernetes.
What seniority level is this role?
Tavus targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Software Engineer, Infrastructure role at Tavus.

From the original posting

About Us

Tavus is a research lab pioneering human computing. We’re building AI Humans: a new interface that closes the gap between people and machines, free from the friction of today’s systems. Our real-time human simulation models let machines see, hear, respond, and even look real—enabling meaningful, face-to-face conversations. AI Humans combine the emotional intelligence of humans with the reach and reliability of machines, making them capable, trusted agents available 24/7, in every language, on our terms.

Imagine a therapist anyone can afford. A personal trainer that adapts to your schedule. A fleet of medical assistants that can give every patient the attention they need. With Tavus, individuals, enterprises, and developers can all build AI Humans to connect, understand, and act with empathy at scale.

We’re a Series B company backed by world-class investors including Sequoia Capital, Y Combinator, and Scale Venture Partners.

Be part of shaping a future where humans and machines truly understand each other.

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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