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Forward Deployed Engineer - Python

Scaling Theory Technologies
2 - 5 Years
Bangalore

Posted on: 30/09/2026

Job Description

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 fast-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.

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