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As an AI Infrastructure Engineer, you will manage user-facing services, ensure system reliability, and improve infrastructure using automation tools such as Ansible and Terraform while collaborating with various stakeholders.

Build and ship customer-facing visibility features (events, audit logs, timelines, notifications, analytics) for Together's Cloud. Partner with Data Platform and Observability teams to implement data collection and processing, own scoped backend work end-to-end, write well-tested backend and product code, and maintain data freshness, completeness, and correctness for trustworthy customer insights.

Build, profile, and optimize Together AI's large-scale training infrastructure. Integrate and validate new model architectures, eliminate performance bottlenecks across compute/memory/communication, and productionize research methods. Enable reliable, scalable fine-tuning for customers and maintain experimental infrastructure to accelerate research-to-production workflows.

The Solutions Architect will act as a technical advisor, collaborate on AI solutions, run demonstrations, and ensure customer success by integrating technical solutions with business needs.

Lead the design of AI developer tools: own end-to-end product UX, evolve and maintain a production design system, conduct user research, prototype and ship features, and partner with engineering and product to ensure high implementation quality and cross-product consistency.

Lead and coach the SRE team, manage on-call rotations, build and operate infrastructure using Ansible, Terraform, and Kubernetes, implement monitoring and observability, design operational processes, debug production issues, and plan scalable infrastructure growth to ensure high availability and reliability for user-facing services.

Work with customers to design, demo, and deploy generative AI applications using open-source LLMs and Together AI's stack. Run complex POCs, collaborate with sales, provide product and engineering feedback, and create educational content and tooling to enable successful deployment and scaling.

The Infrastructure Design Engineer will design and execute whitespace environments for AI data centers, ensuring optimal power, cooling, and networking support. Responsibilities include collaborating with engineers and contractors, creating CAD/BIM models, and overseeing project compliance with engineering standards.

Serve as the named technical owner for a strategic customer, managing end-to-end GPU infrastructure (compute, networking, storage, facilities). Lead incident lifecycle, RCAs, RMA coordination, observability, capacity expansions, and cross-functional escalation while driving technical roadmaps and executive communications.

The Customer Support Engineer will resolve technical challenges for customers involving AI solutions, collaborating with internal teams to improve offerings and ensure customer satisfaction.