The mandate: Serve as the technical partner for enterprise customers deploying and scaling AI voice agents in production — integration design, troubleshooting, workflow building, and expansion from onboarding onward.
The role sits at the intersection of software engineering, customer success, and AI deployment. Works with Engineering, Product, and Customer Success internally, and directly with customer engineering teams.
Relationship to the Applied AI Engineer req (same department):
Applied AI Engineer****Customer Success EngineerComp$200–300K + meaningful equity$65–75/hr, no equityEmploymentFull-time employee1099 or W-2 contractExperience2+ years5+ years CS/CSE, or recent top-tier gradInterview loopNot statedNot stated
Responsibility lists overlap substantially: technical onboarding, debugging across APIs/webhooks/SIP/telephony/auth/latency, working in customer codebases, product feedback, expansion. Confirm with Retell how the two seats are distinguished.
Experience requirement is a barbell: either 5+ years in Customer Success or as a CSE at a B2B software company, or a recent graduate from a top-tier university with a relevant technical degree. No middle band specified.
What You'll Own
Enterprise customer deployments
- Lead technical onboarding for enterprise customers
- Primary technical point of contact throughout implementation
- Drive successful launches and product adoption
- Build relationships with customer engineering teams
Technical consulting
- Build AI voice agents alongside customers
- Design conversation flows and deployment strategies
- Troubleshoot production deployments
- Debug APIs, webhooks, SIP, telephony, authentication, integrations, and latency issues
- Work directly inside customer codebases when necessary
Product partnership
- Identify product gaps through customer feedback
- Translate customer needs into actionable product improvements
- Partner with Product and Engineering; advocate for customers in the development process
Customer growth
- Identify expansion opportunities
- Help customers launch new AI use cases
- Increase adoption across organizations
- Serve as trusted technical advisor for enterprise accounts
Requirements
Hard gates:
- Bachelor's in CS, CE, EE, or a related technical field
- One of: 5+ years in Customer Success or as a CSE at a B2B software company, or recent graduate from a top-tier university in a relevant technical field
- Strong technical problem-solving skills
- Experience working with APIs and debugging technical issues
- Excellent communication; able to explain technical concepts to customers
- Available for standard U.S. business hours in Pacific or Eastern time, with sufficient Pacific overlap
Nice to have:
- Python or TypeScript
- AI, LLM, or voice AI experience
- Startup experience
- Enterprise customer support experience
- Willingness to travel up to 10% for launches, workshops, and Innovation Day events
Not listed but recurring in the responsibilities: telephony, SIP, and real-time communications experience appears throughout the debugging scope.
Anti-patterns
- Traditional CSMs with no debugging ability — the role works inside customer codebases
- Support engineers who escalate rather than diagnose
- Candidates who require full-time employment, benefits, or equity
- Candidates with comp expectations at the Applied AI Engineer band
- Candidates with 2–4 years of experience — excluded by the barbell as written
- Candidates outside Pacific or Eastern time zones
Who Will Thrive Here
Either an experienced CSE working on contract terms by preference, or a recent technical graduate. Both need debugging depth, direct customer communication ability, and comfort working in unfamiliar codebases under production pressure. The JD's framing: "You like building alongside customers instead of just supporting them" and "You're comfortable debugging complex systems under pressure."