Senior AI-Driven Enterprise Deployment Engineer

Madrona Venture Labs; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Deepgram seeks an engineer to own enterprise deployments for restaurants, embedding with customer teams and leading technical solutioning from discovery to go‑live. You will design integrations, troubleshoot live systems, and ensure scalable, repeatable deployments that deliver measurable value.

You will work directly with customers, leverage AI tools, and translate field feedback into product improvements while maintaining fast, reliable delivery in a dynamic startup environment.

Qualifications

• Technical depth across APIs, SDKs, webhooks, cloud infrastructure
• Deep customer empathy and commitment to successful deployments
• Ability to learn rapidly, adapt to ambiguity and move forward with minimal guidance
• Strong communication to align technical and non-technical stakeholders

Responsibilities

• Embed with customer engineering teams as a trusted technical peer and lead discovery and solutioning.
• Own end-to-end technical implementation for enterprise deployments from scoping to go-live and optimization.
• Configure and customize the platform to meet customer operational requirements (ordering flows, POS integrations, edge cases).
• Monitor, troubleshoot, and resolve live deployment issues; escalate complex problems when needed.
• Codify deployment patterns into tools, playbooks, and reference architectures for reuse.
• Translate field learnings into actionable product and engineering requirements; be the voice of the customer.

Skills

Technical depth

Customer obsession

High slope

Communication & trust

Job description

Deepgram seeks an engineer to own enterprise deployments for restaurants, embedding with customer teams and leading technical solutioning from discovery to go‑live. You will design integrations, troubleshoot live systems, and ensure scalable, repeatable deployments that deliver measurable value.

You will work directly with customers, leverage AI tools, and translate field feedback into product improvements while maintaining fast, reliable delivery in a dynamic startup environment.