The mandate: Work directly with enterprise customers to design, build, and deploy production AI voice applications — sitting at the intersection of AI, software engineering, and customer success. The line worth pulling into outreach: "Work directly in customer codebases when needed." That's the difference between this and a solutions engineering job. You're not advising from the outside; you're in their repo. What You'll Own Build AI solutions with customers
-
Design, build, and deploy production AI voice applications
-
Partner with customer engineering teams on Retell API and SDK integration
-
Custom workflows, automations, and conversational AI experiences
-
Architect scalable AI systems for production Solve complex technical problems
-
Debug production issues across APIs, webhooks, telephony, SIP, authentication, latency, and infrastructure
-
Investigate AI behavior; improve prompt quality, reliability, and performance
-
Work directly in customer codebases
-
Own implementation from POC through production launch Drive customer success
-
Lead technical onboarding for enterprise customers
-
Primary technical advisor during implementation
-
Guide on AI best practices, architecture, deployment strategy
-
Expand customers into new AI use cases Influence the product
-
Partner with Product and Engineering to improve the platform
-
Turn customer feedback into product improvements
-
Identify recurring pain points, propose scalable solutions
-
Define best practices for enterprise voice AI deployment Requirements Hard gates:
-
Bachelor's in CS, CE, EE, or a related technical field. Required, no equivalent-experience clause — same pattern as the Founders Initiatives reqs. Worth pushing on.
-
2+ years software engineering or customer-facing technical experience building and deploying production applications
-
Strong Python or TypeScript
-
APIs, SDKs, and distributed systems experience
-
Excellent debugging — the core of the job
-
Strong communication with technical customers
-
Standard U.S. business hours with Pacific Time overlap Profile:
-
3–7 years realistically, given the band
-
Enjoys owning projects architecture through deployment
-
Comfortable wearing engineering, product, and customer success hats
-
Excited about AI and experiments with new models Strong bonuses:
-
AI or LLM-powered application experience
-
Voice AI, speech technologies, or conversational AI — rarest and most directly relevant
-
Cloud infrastructure — AWS, GCP, Azure
-
Telephony, SIP, Twilio, or real-time communications. Named in both the responsibilities and the nice-to-haves, which makes it the highest-signal bonus. Debugging SIP is not something you pick up quickly.
-
Startup experience
-
Customer-facing engineering, solutions engineering, or consulting background
-
Willing to travel up to 10% Location and visa:
-
Redwood City (pending remote clarification)
-
Sponsorship: H-1B, TN, L-1, E-3, F-1 (OPT/CPT), and O-1 Anti-patterns
-
Solutions engineers who demo and hand off. This role writes code in customer repos.
-
Backend engineers with no customer tolerance — technical onboarding and advisory are half the job
-
Support engineers who escalate rather than diagnose
-
Anyone who needs a reproducible bug report before starting
-
Consultants who produce recommendations rather than working systems
-
Engineers uncomfortable with ambiguity in someone else's codebase
-
Career customer success managers with light technical skills Who Will Thrive Here
Someone who likes the puzzle of a production system misbehaving in a customer's environment and has the patience to sit with a VP of Engineering while solving it. They can read an unfamiliar codebase, trace a failure across a webhook and a SIP trunk and a prompt, and explain what happened without condescension. They want breadth — engineering, product input, and customer relationships — rather than depth in one system.