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Mid-Level Full Stack Developer (AI Customer Service Platform)

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Hybrid

Mid-Level Full Stack Developer (AI Customer Service Platform)

EXZEON SDN BHD

Mid-Level Full Stack Developer (AI Customer Service Platform)

Skills

NodePostgreSQLRedisAIAWSn8nJavascript

4 days ago

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Important information


Contract type:

Permanent

Salary:

MYR 72,000 – MYR 84,000 / year

Location:

Kuala Selangor, Selangor, Malaysia

Work mode:

Hybrid

Published on:

15 October 2026

What they need


Key Responsibilities

  • Build, maintain and debug n8n workflows, including sub-workflows, Execute Workflow nodes, AI Agent nodes with tool calling and queue mode.
  • Trace execution logs to the root cause of a problem instead of patching symptoms.
  • Design and tune LLM prompts for structured JSON output, intent classification and confidence thresholds, and move logic out of prompts and into code where that is more reliable.
  • Manage per-merchant configuration, credentials, Redis caching and LLM provider routing and fallback across tenants.
  • Maintain integrations with Chatwoot (inboxes, agent bots, HMAC identity validation), Telegram, web livechat and merchant APIs and webhooks.
  • Work on receipt parsing, bank account matching and reconciliation for deposit and withdrawal flows.
  • Build and maintain logging, reporting and monitoring so failures are visible quickly.
  • Make sure the system fails to a human agent and never to a wrong answer.
  • Write and maintain runbooks, workflow documentation and architecture notes.
  • Make careful, reversible production changes: test before release and have a rollback plan.

Requirements

  • 3–5 years of full stack or backend development experience.
  • Hands-on n8n experience: Code nodes, Execute Workflow, expressions, paired items and null handling.
  • Strong JavaScript skills (data transformation, string matching, debugging).
  • PostgreSQL: joins, jsonb, upserts (ON CONFLICT) and safe UPDATE/DELETE practice.
  • REST API integration: authentication schemes, headers, webhooks and error handling.
  • Experience with an LLM API (OpenAI, OpenRouter or similar), including prompt engineering for structured output.
  • Comfortable with Git and systematic debugging.
  • Strong problem-solving skills and ability to work independently.
  • Fluent in English and Bahasa Malaysia.

Nice-to-Haves

  • RAG fundamentals: embeddings and vector similarity.
  • Redis caching (TTLs, invalidation).
  • Chatwoot administration.
  • AWS basics (ECS, NAT egress IPs, IP whitelisting).
  • Experience with multi-tenant system design.
  • Mandarin

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