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FlexAI

On-demand GPU clusters for AI workloads

Senior Backend Engineer

Backend EngineeringConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USA$180k - $225k /yr

About the Job

Requirements

  • At least 5 years of backend or infrastructure engineering experience.
  • Expert-level, hands-on proficiency in Golang.
  • Strong experience building production-grade distributed systems.
  • A proven track record with infrastructure platforms, platform as a service, or deep-tech systems.
  • Deep understanding of cloud-native architectures and containerized environments.
  • Strong experience with Kubernetes, Docker, and cluster orchestration.
  • Experience with distributed databases such as PostgreSQL, Cassandra, or DynamoDB.
  • Strong understanding of caching, queues, and streaming systems such as Redis and Kafka.

Responsibilities

  • Architect and develop high-performance Golang services for the AI platform-as-a-service and infrastructure platform.
  • Build internal application programming interfaces for model deployment, job scheduling, and compute lifecycle management.
  • Develop components that interface with GPU and compute infrastructure and AI runtimes.
  • Design and scale microservices and event-driven systems for high-throughput AI workloads.
  • Optimize systems for low latency, high concurrency, and fault tolerance.
  • Implement service-to-service communication using gRPC, REST, message queues, and asynchronous pipelines.
  • Drive reliability, observability, and resilience across services.
  • Collaborate with AI/ML and Runtime teams to integrate systems with training pipelines, inference infrastructure, experimentation workflows, and dataset and artifact management.
  • Enable orchestration across cloud and on-premises environments.
  • Build abstractions that simplify consumption of AI infrastructure.
  • Design cloud-native, Kubernetes-native services.
  • Work with DevOps/SRE on continuous integration and continuous delivery, deployment automation, and scalability.
  • Contribute to architecture decisions for multi-region, multi-cloud infrastructure.
  • Improve monitoring, logging, and diagnostics.
  • Lead architecture reviews and set engineering standards.
  • Mentor engineers and guide complex problem-solving.
  • Drive the long-term roadmap for backend infrastructure and AI platform capabilities.
  • Partner with Product, Runtime, and Infrastructure leadership to translate requirements into scalable systems.

Desired Qualifications

  • Familiarity with compute scheduling, resource management, or platform runtimes.
  • Experience on AI/ML platforms, model infrastructure, or data platforms.
  • Familiarity with machine learning pipelines, inference systems, or GPU-backed workloads.
  • Exposure to PyTorch, TensorFlow infrastructure, or model-serving systems.

About the Company

FlexAI

On-demand GPU clusters for AI workloads

FlexAI provides a Workload as a Service (WaaS) platform that gives AI developers on-demand access to scalable GPU compute for the full AI lifecycle, including training, fine-tuning, and inference. The platform lets users spin up GPU clusters quickly and run workloads in parallel, with automated scaling to optimize resource use and costs. It also supports performing multiple fine-tuning runs across different datasets and models at the same time, enabling rapid experimentation while the platform handles infrastructure management. This differentiates FlexAI from competitors by offering serverless, pay-per-use AI-optimized compute that abstracts away hardware setup and maintenance, focusing users on building and deploying models. The company aims to accelerate AI initiatives for developers, data scientists, and organizations by delivering cost-efficient, scalable compute without the overhead of managing their own GPUs.

Company size
51-200
Company stage
Seed
Total funding
$30M
Headquarters
Paris, France
Founded
2023

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