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DocuSign is seeking a Cloud Platform Engineer to join their infrastructure and DevOps team in San Francisco. This is a hands-on individual contributor role reporting to the Director of DevOps Engineering, focused on building and operating scalable cloud infrastructure, tooling, and automation that enables product teams across the organization.
You will write production-quality code (Python, Go) to develop tools and automation that improve platform accessibility and engineer productivity. Key responsibilities include designing and implementing shared infrastructure components for availability and scalability, building production-ready AI services within cloud platforms (including LLM-powered and agentic workflows), and developing infrastructure-as-code using Terraform or Ansible across multi-cloud environments (AWS, Azure, GCP).
The role emphasizes AI-native engineering practices—you'll use AI coding assistants as force multipliers and help integrate scalable AI capabilities into the cloud foundation for secure, efficient adoption across teams. You'll participate in on-call rotations, contribute to incident response and root-cause analysis, and support services across their full lifecycle with a focus on system design, self-service capabilities, scalability, and reliability.
Additional responsibilities include implementing security controls and Zero Trust practices in partnership with InfoSec, monitoring cloud environments using Datadog and Grafana, and optimizing resource utilization for cost efficiency.
Required qualifications: BS/BA in Computer Science, Engineering, IT, or related field (or equivalent experience); 5+ years in Cloud Engineering, DevOps, Platform, or Infrastructure Engineering; production-quality code experience in Python and/or Go; experience with LLMs, prompt engineering, and AI agent frameworks; scripting and automation skills (Python, Bash, PowerShell); cloud resource management (AWS, Azure, GCP); IaC tools (Terraform, Ansible); and CI/CD pipeline experience.
Preferred: hands-on experience building or operating LLM-powered or agentic services in production (RAG, model routing, orchestration); containerization and orchestration (Docker, Kubernetes); Linux/Windows administration; monitoring and AIOps tooling; network architecture and security best practices; and strong problem-solving and communication skills.
