Solutions Architect - Infrastructure

Decagon Decagon · Vertical AI · San Francisco, CA · Sales

Solutions Architect - Infrastructure role at Decagon, a conversational AI platform company. Focuses on pre-sales engineering, deployment architecture, and enterprise infrastructure strategy for integrating Decagon's AI platform into customer environments. Requires experience with containerization, cloud functions, and enterprise infrastructure, with a preference for AI/ML infrastructure solutions experience.

What you'd actually do

  1. Partner with Account Executives to discover, qualify, and design deployment solutions that address customer infrastructure constraints and deliver measurable ROI.
  2. Navigate ambiguous conversations with customers about their infrastructure landscape, translating diverse environments (GCP, AWS, hybrid, on-prem) into clear integration and deployment strategies for Decagon's platform.
  3. Design containerization approaches, cloud function implementations, and infrastructure architectures tailored to each customer's unique requirements and security posture.
  4. Establish scalable pre-sales processes, deployment playbooks, and reusable reference architectures to support growth.

Skills

Required

  • 8–10+ years of experience in customer-facing technical roles such as Solutions Architect, Solutions Engineer, or Technical Account Manager with a focus on infrastructure and deployment.
  • Deep fluency in containerization (Docker, Kubernetes), GCP Cloud Functions/Cloud Run, and AWS architecture patterns—with the ability to adapt recommendations to customer constraints.
  • Demonstrated success navigating ambiguous technical conversations with enterprise customers, asking the right discovery questions, and collaborating through uncertainty.
  • Strong ability to engage with diverse stakeholders—from platform engineers to CISOs to business leaders—and translate infrastructure requirements into actionable deployment strategies.

Nice to have

  • 2+ years of experience selling or architecting AI/ML infrastructure solutions in enterprise environments.
  • Experience working in a high-growth startup environment where you've built pre-sales infrastructure practices from the ground up.
  • Hands-on experience with infrastructure-as-code (Terraform, Pulumi), service mesh technologies, or multi-cloud deployment patterns.
  • An engineering background (DevOps, Platform Engineering, SRE, or software engineering) that enables you to dive deep into technical architecture and troubleshooting conversations.

What the JD emphasized

  • customer infrastructure constraints
  • ambiguous conversations
  • infrastructure landscape
  • customer's unique requirements
  • ambiguous technical conversations
  • infrastructure requirements