PR/123175 | Founding Engineer (Engineer Lead / CTO)

Our client is a new stealth startup in Indonesia that are currently looking for a Founding Engineer with hands-on GenAI builder experience to ship LLM-powered customer support automation (RAG + LangChain + WhatsApp/Shopee APIs) from scratch.

Key Requirements:

• Proven track record building and shipping LLM-powered applications end-to-end (not just research/POCs).

• Expertise with RAG pipelines, LangChain or LlamaIndex, and vector databases (Pinecone, Weaviate, FAISS, Milvus).

• Strong Python development (FastAPI, PyTorch/TensorFlow, Hugging Face).

• Experience integrating LLMs into production systems (chatbots, copilots, customer-facing workflows).

• Familiarity with 3rd-party APIs (WhatsApp, TikTok, Shopee, Shopify, Zendesk).

• Comfortable with 0→1 building in early-stage environments; able to balance speed with scalability.

• CS/adjacent degree or equivalent coding expertise; strong problem-solving and debugging skills.

• Stability in past roles; clear evidence of recent hands-on builds.

• Willing to start hands-on coding full-time, with a path to CTO as the company scales (hiring/managing engineers, shaping tech vision).

Key Responsibilities: 

Design & Build the AI Core

Develop the intelligence layer using LLMs (OpenAI, Anthropic, Gemini, etc.) for e-commerce customer support workflows (order tracking, refunds, cancellations, shipping status).

End-to-End Automation Engine

Implement RAG pipelines, vector search, and conversational flows.

Build automation that can independently query APIs (Shopee/TikTok/WhatsApp) and execute actions like refunds, order updates, etc.

Integrate with Commerce Platforms

Connect AI workflows with e-commerce APIs (example: Shopee, Tokopedia, TikTok Shop) and messaging platforms (WhatsApp Business).

Build the User Experience for Sellers

Develop the interface where sellers can:

• Monitor AI conversations.

• Intervene when needed

• Manage customer interactions in one place.

Product Iteration & Feedback Loops

Deploy MVP with first e-commerce pilot users.

Collect data & feedback to refine conversational accuracy, workflow automation, and user trust.

Technical Leadership

Define the AI technical vision & architecture.

Own decisions on LLM frameworks, vector DBs, orchestration tools.

Establish coding standards, infra setup, and security.

Future Scaling

Transition from sole contributor → team leader / CTO.

Recruit, mentor, and lead engineering hires as company scales.