Together AI→
Software Engineer - Storage & Observability… at Together AI · San…
Entry LevelOn-siteFull-timeSan Francisco$165k–$200k/yr
Skills
gopythonkubernetesterraformdistributed storagedockergitprometheusgrafana
Job Description
Summary: Together AI is a research-driven artificial intelligence company focused on building the AI Acceleration Cloud. They are seeking an Early Career Software Engineer to join their Storage and Observability team to design and maintain distributed storage solutions and develop observability platforms for AI workloads.
Responsibilities:
- Build and deploy scalable observability tools (metrics, logs, traces) using the latest state of the art open source distributed telemetry, log search and tracing systems
- Develop and implement infrastructure-as-code for stack deployment using Terraform, Ansible, and Helm
- Write clean, production-grade code in Go or Python to create custom K8S operators, tools and automation
- Support the operation of high-performance distributed storage systems (such as Ceph, Weka/Vast) and Kubernetes-native storage operators
- Optimize storage systems for GPU clusters (10-50 GB/s per-node throughput) and scale storage infrastructure to support thousands of nodes
- Partner with senior engineers to enhance distributed tracing and optimize data paths for AI workloads
Required Qualifications:
- 1–3 years of professional experience in Software Engineering or Cloud Operations with hyper scalers
- Solid understanding of Docker and Kubernetes orchestration, as well as experience with cloud platforms like AWS, GCP, or Azure
- Familiarity with infrastructure-as-code (Terraform or Helm) and version control (Git)
- Experience using Prometheus and Grafana for system monitoring
- Experience with distributed storage systems, like WekaFS, Vast, Ceph, MinIO, GPFS, Luster etc
- Strong debugging skills and a passion for automation and operational excellence
Preferred Qualifications:
- Experience monitoring AI/ML infrastructure, GPU clusters, and custom metrics for model performance and training pipelines
- Background in high-frequency, low-latency systems monitoring, chaos engineering, and reliability testing
- Contributions to open-source projects, preferably in the space of observability or storage
- Familiarity with security monitoring and compliance frameworks
Required Skills: Go, Python, Kubernetes
Important Skills: Terraform, Distributed storage, Docker
Nice-to-Have Skills: Git, Prometheus, Grafana
Benefits: Competitive compensation, Startup equity, Health insurance, Flexibility in terms of remote work, Benefits
Benefits
Competitive compensation
Startup equity
Health insurance
Flexibility in terms of remote work
Benefits