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About the Role: Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure. As a Senior Backend Engineer, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal StaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world. Some of what you’ll work on: Work on a distributed GPU scheduling system for the on-demand clusters product, Instant Clusters; Build out a global management plane for managing our data center compute, networking, and storage; Design and build new customer-facing cloud platform services, delivering killer enterprise AI cloud features.
Job Responsibility:
Identify, design, and develop foundational backend services that power Together’s cloud platform
Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
Partner with product teams to understand functional requirements and deliver solutions that meet business needs
Write clear, well-tested, and maintainable software and IaC for both new and existing systems
Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
Participate in an on-call rotation to address critical incidents when necessary
Requirements:
5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems and API microservices
Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members
Demonstrated experience with building and operating high-performance and/or globally distributed microservice architectures across one or more cloud providers (AWS, Azure, GCP)
Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale
Experience developing against and managing a relational database, such as PostgreSQL
Expert-level programmer in one or more of programming language (Golang preferred)
Proficiency in version control practices and integrating IaC with CI/CD pipelines
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
Nice to have:
Experience with Kubernetes and containers preferred
Experience building and operating data infrastructure (Kinesis, Airflow, Kafka, etc) a plus