Staff Platform Engineer

Staff Platform Engineer Sanas is pioneering the future of human communication. Founded by a team of Stanford researchers and entrepreneurs with deep industry experience, Sanas has developed the world's first real-time speech AI platform capable of accent translation, noise cancellation, speech enhancement, cross-language communication, and more. Sanas makes conversations clearer, more inclusive, and more effective, removing barriers that prevent people from being understood, regardless of accent, background noise, or native language. Sanas is currently one of the fastest growing startups in Silicon Valley, growing from $16M to $50M ARR in 2025. The company's core business is profitable and is on track to end 2026 with >$120M ARR. Our team combines deep expertise in model innovation and systems engineering with a design-minded product engineering culture to build and ship cutting-edge AI models and experiences — entirely in-house. Sanas is a 180-strong team, established in 2020. In this short span, we've successfully secured over $100 million in funding. Our innovation has been supported by the industry's leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you're not just adopting a product; you're investing in the future of communication. If you're looking to have a significant role in roadmapping and driving technical directions, if you're looking to deploy challenging and big ideas without much overhead or slowness, if you're looking to leave your mark on an ambitious, generational mission to change how the worlds thinks about speech + AI, then Sanas is a well-suited place for you. About the Role We're looking for an experienced Platform Engineer to build and operate the hybrid infrastructure foundation for our advanced AI/ML research and product development. You'll architect, build, and run our platforms spanning AWS and on-premise deployments, empowering our teams to train and deploy complex models at scale. This role is focused on creating a robust, self-service environment using Kubernetes, AWS, and Infrastructure-as-Code (Terraform), and orchestrating high-demand GPU workloads. Job Description Architect and maintain our core computing platform using Kubernetes on AWS and on-premise, providing a stable, scalable environment for all applications, research initiatives, and Sanas services. Provision, manage, and maintain our on-premise bare metal server infrastructure for high-performance GPU computing. Lead comprehensive observability across the organization (monitoring, logging, tracing) to ensure platform(s) health, and create automation for operational tasks, incident response, and performance tuning. Design and build low latency, scalable, and reliable infrastructure that serves model inference and training for our cutting-edge speech AI models. Collaborate with AI researchers and ML engineers to understand their infrastructure needs and build the tools and workflows that accelerate and support their development cycle. You'll have significant autonomy to shape our product infrastructure, and directly impact how cutting-edge AI is applied across various devices and applications in speech. Qualifications 5+ years of Software Engineering experience, preferably in Platform Engineering or Site Reliability. Strong fundamentals with a focus on writing clean & maintainable code. Strong proficiency in scripting (Bash), Python, or Rust. Experience building large-scale distributed systems with high demands on model inference, performance, reliability, and observability. Experience with high-performance compute (HPC) schedulers, capacity planning, containerized deployments, and familiarity in managing GPU-intensive AI workloads. Strong communication skills with ability to own large scope projects by working cross-functionally across Engineering, AI, Product, Research and Business stakeholders. Experience working with AWS (preferred), GCP or Azure, EKS / Kubernetes. Deep curiosity about the state of agentic coding tools and how to optimize agent-assisted workflows.

Bonus Nice-to-have:

Familiarity with real-time streaming protocols like WebTransport and

SIP/SRTP.

Bachelor's Degree in Computer Science or related fields. Apply now Engineering Palo Alto, CA Share on: Apply now