Support Engineering Lead

Support Engineering Lead

As a Support Engineering Lead at Retell, you will own the technical support function for a highly technical, agentic voice AI platform. This is a hands-on leadership role: you will personally debug complex customer issues, build AI agents and automations, and lead a growing team of support engineers.

You will operate at the intersection of engineering, customers, and product, ensuring world-class reliability, fast resolution, and scalable support economics as Retell grows.

This role is ideal for someone who enjoys solving hard technical problems under pressure, working directly with customers, and building systems and teams from the ground up.

Support Fundamentals

• Own end-to-end resolution of complex support tickets for a production, agentic AI platform.
• Debug issues across agents, prompts, APIs, webhooks, logs, integrations, and telephony.
• Build, configure, and test AI agents to reproduce and resolve customer issues.
• Join live customer calls when needed to diagnose problems and restore confidence.
• Own core support metrics including CSAT, NPS, SLA, and response times.
• Define and improve support unit economics, including automation vs headcount tradeoffs.

Automation & Tooling

• Design and build AI-driven support workflows and automations to reduce manual load.
• Develop internal tools and dashboards for the support team with appropriate permissions and access control.
• Improve observability, alerting, and debugging workflows to shorten time-to-resolution.
• Identify recurring issues and turn them into automations, tooling, or product improvements.

Team Leadership & Management

• Recruit, interview, onboard, and mentor support engineering team members.
• Set quality bars, escalation guidelines, and on-call processes.
• Run weekly analysis of feature requests, bug trends, and documentation gaps.
• Partner closely with Engineering and Product to influence roadmap and reliability priorities.

Product & Feedback Loop

• Translate customer pain points into clear, actionable feedback for Product and Engineering.
• Help shape documentation, best practices, and customer-facing guidance.
• Act as a voice of the customer while maintaining technical rigor and operational discipline.

You Might Thrive If

• Have 3+ years of experience in technical support, support engineering, solutions engineering, systems engineering, or similar roles.
• Have supported a technical, developer-facing product in production.
• Have 1+ year of experience at a startup, ideally in a support engineering role.
• Are comfortable writing and debugging code (Python & JavaScript) for real use cases.
• Have built or configured AI agents, workflows, or LLM-powered systems.
• Are highly detail-oriented and calm under pressure when incidents occur.
• Think analytically about metrics, root causes, and system-level improvements.
• Communicate clearly with both technical and non-technical stakeholders.

Job Details

• Cash: $170,000 - $230,000 base salary
• Equity: Offers Equity
• Location: Redwood City, CA, US (Relocation Provided)
• US Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H1B/H-1B, TN, L-1, E-3, F-1 (OPT/CPT), and O-1 visas.

Other Benefits

• 100% coverage for medical, dental, and vision insurance
• $70/day DoorDash credit for unlimited breakfast, lunch, dinner, and snacks
• $200/month wellness reimbursement (gym, fitness classes, etc.)
• $300/month commuter reimbursement (gas, Caltrain, etc.)
• $75/month phone bill reimbursement
• $50/month internet reimbursement

Compensation Philosophy

• Best Offer Upfront: Choose from three cash-equity balance options, no negotiation needed.
• Top 1% Talent: Above-market pay (top 5 percentile) to attract high performers.
• High Ownership: Small teams, >$1M revenue/employee, and significant equity.
• Performance-Based: Offers tied to interview performance, not experience or past salaries.

Interview Process

1. Recruiter Intro Call (15min): Learn about us and share your background.
2. Technical First Round (45 min): Live debugging exercise in real a world scenario
3. Onsite (3 hours)