Support Engineer (Contract)

Retell AI•San Francisco, CA

7d•$6,000 - $7,500•Remote

About The Position

Retell AI is hiring a Support Engineer to serve as a technical partner to enterprise customers, helping them launch and maintain voice agents. The role involves building alongside customer engineering teams, debugging production issues, and translating customer experience into product improvements. The engineer works with Engineering, Product, and Customer Success, as well as customer developers, IT teams, and telephony providers. The position leads enterprise technical onboarding from kickoff and architecture review through go-live and ramp, helps customers move from pilot to production, and supports concurrency planning, load readiness, and rollout strategy. It also involves configuring voice agents, designing integrations with customer systems, advising on conversation design and deployment, and working in customer codebases when needed. The engineer troubleshoots live deployments across call quality, latency, interruptions, transcription, agent behavior, APIs, webhooks, authentication, telephony, and custom LLM integrations. They use call logs, transcripts, and post-call analysis to identify root causes, communicate incident findings, and escalate reproducible issues to Engineering. The role also captures customer feedback, develops documentation and playbooks, and helps test new features with customers. This is a remote, full-time 1099 contract role requiring meaningful overlap with Pacific Time working hours. Compensation is $6,000–$7,500 USD per month, based on experience.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
2–8 years of professional experience in Technical Support Engineering, Customer Success Engineering, Solutions Engineering, Forward Deployed Engineering, Software Engineering, or a similar technical role.
Strong technical problem-solving skills and comfort debugging distributed systems.
Hands-on experience with REST APIs, webhooks, and authentication, and with reading logs and network traces to find root causes.
Clear written and live communication skills, including the ability to explain technical issues to developers and business stakeholders.
Comfort working directly with customers, including during live launches and incidents.
Availability for meaningful overlap with Pacific Time working hours.

Nice To Haves

Python or TypeScript experience.
Experience with LLMs, prompt engineering, voice AI, or conversational AI platforms.
Telephony knowledge, including SIP, VoIP, PSTN, and providers such as Twilio or Telnyx.
Familiarity with latency optimization, speech-to-text and text-to-speech, or real-time WebSocket systems.
Startup experience and enterprise customer experience, including security reviews and compliance questions such as SOC 2 and HIPAA.
Willingness to travel occasionally for launches or onsite work.

Responsibilities

Lead technical onboarding for enterprise accounts, from kickoff and architecture review through go-live and ramp.
Help customers move from pilot to production, including concurrency planning, load readiness, and rollout strategy.
Build trusted relationships with customer engineering, IT, and security teams.
Build voice agents with customers in Retell, including prompts, conversation flows, knowledge bases, voice and language settings, and call transfers.
Design integrations with customer systems such as CRMs, scheduling tools, ticketing systems, and internal APIs using custom functions, webhooks, the Retell API, and SDKs.
Advise on conversation design and deployment strategy for use cases such as inbound support, outbound campaigns, appointment booking, and qualification.
Work directly in customer codebases when needed.
Troubleshoot live deployments, including call quality, latency, interruptions and turn-taking, transcription errors, hallucinations, tool-call failures, and unexpected agent behavior.
Debug APIs, webhooks, authentication, SIP trunking and telephony, and custom LLM integrations.
Use call logs, transcripts, and post-call analysis to identify root causes and write clear post-incident summaries for customers.
Escalate issues to Engineering with reproducible cases and the context needed to resolve them.
Capture customer feedback and turn it into specific, prioritized product requests.
Identify recurring issues and create documentation, templates, and playbooks to prevent them from recurring.
Work with Product and Engineering to test new features with real customers.