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TensorWave
Development 4d ago

Full Stack Engineer

TensorWave
United StatesUnited States
Full-time
Not Disclosed
Mid-Level

Job Description

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GraphQLGo (Golang)

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At TensorWave, we're revolutionizing AI computing by offering the most advanced cloud services, highlighted by our deployment of AMD Instinct Series GPUs. Our mission is to accelerate AI innovation by removing hardware limitations and ensuring scalable, efficient solutions for AI workloads.

About The Role:

We are looking for a Full Stack Engineer to join our Product Engineering team. You'll build scalable, modern web applications and high-performance backend services that power TensorWave's next-generation AI cloud platform. Working directly with our cloud infrastructure team and UI/UX designers, you will lead the ground-up overhaul of our internal admin and customer-facing dashboards.

This isn't a 'close the ticket and move on' role. We're looking for problem solvers and owners who take full responsibility for what they build, dig into issues until they're truly solved, and consistently go above and beyond to deliver real value to our customers.

What You'll Do:

  • Lead the architecture and ground-up rebuild of our internal administrative tools and customer-facing dashboards.

  • Design and implement frontend applications using React.js and Next.js to provide seamless access to our GPU cloud services.

  • Develop robust APIs to support both multi-tenant cloud architectures and single-tenant, bare-metal deployments.

  • Develop and maintain GraphQL and REST APIs using Node.js, Express.js, and Apollo to handle complex data requirements.

  • Collaborate with the AI infrastructure team to integrate new GPU capabilities into our platform, utilizing Go (Golang) for high-throughput backend components.

  • Own features end to end, from design and implementation through deployment, monitoring, and iteration.

  • Instrument services with OpenTelemetry and build dashboards in Grafana to monitor performance and drive proactive optimization.

Who You Are:

  • An owner: You treat the product like it's yours and take accountability for outcomes, not just tickets.

  • A problem solver: You're energized by hard, ambiguous problems, and leverage first principles thinking to move the needle.

  • Customer-focused: You understand that the work matters because of the value it delivers to our users.

  • Proactive and self-driven: You are a T-shaped engineer who thrives in a lean startup environment; for you, stepping beyond the bounds of your role is second nature because you care deeply about solving hard problems and building resilient AI infrastructure at scale.

Essential Skills & Qualifications:

  • 5+ years of professional software development experience.

  • Strong proficiency in React.js, Next.js (including SSR), and modern frontend development.

  • Strong knowledge of GraphQL and the Apollo ecosystem (Client, Server, schema design).

  • Solid foundation in Node.js and Express.js for building robust web applications.

  • Proven ability to drop into unfamiliar codebases, troubleshoot effectively, and solve complex problems independently.

  • Familiarity with Docker and containerization concepts.

  • Bachelor's degree in Computer Science or equivalent experience.

Preferred Skills & Qualifications:

  • Experience with Go (Golang) for building backend services, or a strong willingness to learn and adapt to Go-based tooling.

  • Experience with MongoDB, database design, and Redis for caching.

  • Understanding of Kubernetes (k8s), cloud infrastructure, and network fundamentals.

  • Experience with observability using OpenTelemetry (OTel) and Grafana-based stacks (PLG/MLG).

  • Python programming skills, particularly with FastAPI.

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TensorWave is a premier, enterprise-grade cloud infrastructure provider engineered to orchestrate massive-scale artificial intelligence (AI) and high-performance computing (HPC) workloads. Operating as a high-velocity digital ecosystem, the company eliminates the operational friction and supply chain bottlenecks of legacy hyperscalers by exclusively deploying advanced AMD Instinct™ accelerators—including the MI300X and MI325X—across highly optimized bare-metal environments. Moving beyond the rigid memory constraints of traditional GPU cloud models, TensorWave provides industry-leading capacity with up to 288GB of HBM3e per accelerator, directly tackling the immense requirements of next-generation Large Language Models (LLMs) and complex machine learning training clusters. Under the hood, their UEC-ready networking architecture and direct liquid cooling systems seamlessly integrate into existing AI pipelines, ensuring ultra-low latency inference and blistering training speeds. What sets TensorWave apart is its uncompromising dedication to open-source democratization and performance accessibility; by bridging the gap between top-tier compute resources and massive cost-efficiency, the platform empowers scaling enterprises to radically accelerate AI innovation without the burden of building internal hardware infrastructure.

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