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Design and implement manifest-driven provisioning and reconciliation systems for GPU hosts and clusters. Build durable workflow engines, declarative self-service APIs, event-driven automation, self-healing pipelines, and production-grade control planes. Own coding, testing, CI/CD, and operate the platform in production to eliminate manual provisioning.

Own full sales cycle for strategic AI-native and enterprise accounts: generate pipeline, close new business, expand customers, and partner with Solutions, Engineering, and Research to run POCs and scale deployments. Provide technical and business insights to inform product and sales strategy.

Provide technical support to customers on AI solutions, resolve complex issues, collaborate with teams, and improve product offerings.

Operate and scale Together AI's production infrastructure: run GPU-enabled Kubernetes clusters, automate with Ansible and Terraform, build monitoring/observability, respond to incidents (on-call), debug production issues, design deployment/upgrade processes, and plan infrastructure growth for high availability and scalability.

As a Senior Developer Productivity Engineer, you will enhance CI/CD processes, optimize workflows, and build tools for efficient software delivery.

The Site Reliability Engineer ensures user-facing services run smoothly, focuses on systems reliability and scalability, and enhances operational practices through automation and engineering principles.

Provide customer-facing SRE/technical support for Kubernetes GPU clusters and HPC environments. Troubleshoot GPU hardware, networking (InfiniBand/RDMA/NVLink), distributed storage (Weka/NFS), Slurm workflows, and container workloads. Maintain cluster health, perform node maintenance and migrations, document procedures, and collaborate with Engineering, Product, and Sales to drive customer success and product improvements. Provide weekend and on-call coverage.

Customer-facing technical role providing SRE-style support for GPU clusters, LLM inference, and fine-tuning. Troubleshoot production incidents, run infra-as-code changes, validate migrations, monitor observability dashboards, and translate technical findings to customers and engineering. Drive improvements by surfacing patterns and maintaining documentation.

Partner with strategic customers to optimize LLM inference and post-training pipelines, tune inference engines for latency/throughput, run and productionize fine-tuning (LoRA, SFT, DPO, RLHF), and feed field insights into product and model roadmaps to ensure successful POCs and deployments.

Provide legal support for infrastructure procurement and enterprise commercial deals. Lead negotiations for GPU/cloud capacity, data center, networking, and vendor agreements; align vendor terms with customer contracts; manage export controls and data/privacy compliance; build templates, playbooks, and scalable procurement and sales workflows; support partnerships, reseller and go-to-market deals; and run procurement processes and vendor template libraries.