Responsibilities :

- Scope and build customer voice workflows on the canvas : pre-call lookups, in-call tools, knowledge bases, transfers, post-call data extraction, and webhooks.
- Write the integrations customers need (REST and webhook glue into CRMs, ticketing, scheduling, and internal systems) and make them robust to retries, timeouts, and bad data.
- Run onboarding end-to-end : discovery calls, prompt and workflow design, Simulation test passes, telephony number setup with the customer's carrier, go-live, and the first weeks of monitoring.
- Debug production calls using our observability stack : latency by STT / LLM / TTS component, end-status breakdowns, tool-call traces and recordings.
- Turn repeated customer asks into product : file precise issues, ship small platform fixes yourself (Python agent runtime, Go APIs), and hand larger ones to the core team with a reproduction.
- Write the runbook and hand-off notes so Customer Success can support the account without you.
- Be on point for your customers during launch windows, including some US-hours overlap for North American accounts.

Requirements :

- 1.5 to 4 years building and running software in production, in a product company or a quick-moving services team.
- Strong in Python; comfortable in TypeScript; willing to read and patch Go.
- Has integrated with third-party APIs for real (auth flows, pagination,



webhooks, idempotency) and knows what breaks when they misbehave.
- Has worked with LLM APIs : prompting, structured outputs, tool/function calling, and evaluating whether a change actually helped.
- Comfortable with Docker, a cloud provider (we use AWS), and reading logs, metrics, and traces to find the cause of a bad call.
- Can sit in a customer call, understand a business process, and translate it into a workflow with clear edge cases, then explain trade-offs in plain language.
- Writes clearly : PRs, issues, runbooks, and customer-facing notes that someone else can act on.
- Bias to shipping. Comfortable owning an outcome with incomplete information and asking for help early.

Bonus Skills :

- Any exposure to voice or real-time systems : LiveKit, WebRTC, SIP, Twilio / Telnyx / Exotel, STT or TTS APIs, streaming audio.
- Built or shipped an LLM agent with tools in production, and dealt with latency, hallucination, or cost trade-offs.
- Go in production, or Kubernetes beyond kubectl apply.
- Worked directly with customers before : solutions engineering, implementation, or a founding-engineer role at an early-stage company.
- Contact-centre, healthcare, or fintech domain knowledge.
- Familiar with ClickHouse, Kafka, or similar analytics pipelines.

📌 Forward Deployed Engineer - Python (India)
🏢 SCALING THEORY TECHNOLOGIES
📍 India