AI Automation Engineer

Vibehackers; Hinoba-an; On-site; PHP 1,000,000 - 1,300,000; Full time

Job summary

Vibehackers is seeking an AI Automation Engineer to design, build, deploy and operate internal applications that automate manual processes across merchandising, production, sourcing, HR, compliance and sustainability. The role focuses on production delivery of LLM-enabled tools and integrations, with responsibility for uptime, documentation and stakeholder adoption.

TypeScript/Node or Python proficiency, React experience, and hands-on work with Docker, Linux, SQL and AI/LLM APIs are highly

Qualifications

• 2–5 years of software development experience with production LLM APIs.
• Proficiency in TypeScript/Node or Python, with familiarity in the other language.
• Experience with APIs, webhooks and third-party system integration.
• Ability to design and deploy end-to-end internal applications and pipelines.
• Strong communication to elicit requirements from non-technical stakeholders.

Responsibilities

• End-to-end design, development and deployment of internal automation tools.
• Document manual processes, assess viability and set automation priorities.
• Develop backend services, user interfaces, authentication and error handling.
• Design workflows, MCP servers, API connectors and RAG pipelines.
• Ensure uptime across VPS and cloud environments and provide training.

Skills

Requirements gathering

Stakeholder communication

Monitoring and cost management

Software delivery

LLM integration

Team collaboration

Tools

Docker

Linux

React

SQL

Node.js

Python

LLM APIs

Job description

Uses LLM APIs, RAG, agent frameworks and retrieval pipelines to build AI-powered internal tooling and automation.

About the Role

The AI Automation Engineer will design, build, deploy and operate internal applications that automate manual processes across merchandising, production, sourcing, HR, compliance and sustainability. The role focuses on applied engineering—delivering multiple production LLM-based tools and integrations each quarter, with responsibility for uptime, documentation and stakeholder adoption.

Job Description

Role

The AI Automation Engineer is responsible for end-to-end design, development, deployment and operational ownership of internal applications that reduce manual effort across the organisation. This is an applied engineering role focused on production delivery of LLM-enabled tools, system integrations and automation pipelines rather than research or model creation.

Representative projects

• ERP intelligence layer (WFX) for conversational access to order status and risk detection.
• Email and document automation: triage, extraction, routing and drafted responses for buyer correspondence and tech packs.
• Compliance documentation pipelines to prepare traceability and audit evidence in buyer-specified formats.
• Design archive search: image tagging and semantic search across the design library.
• ESG and GHG data pipelines: consolidating utility/fuel/production data and emissions calculations with auditable trails.
• Production reporting optimised for mobile access by plant leadership.

Key Responsibilities

• Engage with operational teams to document manual processes, assess automation viability and set priorities.
• Develop and deploy internal applications end-to-end, covering backend services, user interfaces, authentication and error handling.
• Design agent workflows and system integrations, including MCP servers, API connectors, RAG pipelines and structured extraction from documents and images.
• Assume operational responsibility for deployment and uptime across VPS and cloud environments.
• Prepare technical documentation and deliver user training to support cross-department adoption.
• Monitor operating cost per workflow and recommend retirement of solutions where returns do not justify continued investment.
• 2–5 years of software development and delivery experience, including recent production experience with large language model APIs.
• Proficiency in TypeScript/Node or Python, with working familiarity in the other language.
• Demonstrated delivery of an LLM-based application in sustained use, including prompt design, tool/function calling, structured outputs and evaluation methodology.
• Experience with APIs, webhooks, authentication protocols and third-party system integration.
• Ability to develop functional user interfaces (React or equivalent).
• Working knowledge of SQL and experience handling inconsistent or unstructured data.
• Competence in deployment fundamentals: Linux, Docker, environment configuration and logging.
• Strong communication skills and ability to elicit requirements from non-technical stakeholders.
• Exposure to manufacturing, apparel, textile or supply chain systems (ERP, PLM, shop floor applications).
• Experience with vector databases, retrieval pipelines, document AI (OCR, layout parsing) and computer vision for image classification/search.
• Familiarity with MCP, agent frameworks or agentic development tools.
• Exposure to ESG, sustainability or compliance reporting.

TypeScript Node Python React SQL Linux Docker VPS Cloud LLM APIs MCP WFX RAG (retrieval-augmented generation) Webhooks Vector databases OCR Agent frameworks

Skills

Software Development LLM / Prompt Engineering API Integration System Integration Frontend Development SQL / Data Handling DevOps / Deployment Docker Linux Technical Documentation Requirements Gathering Stakeholder Communication Monitoring and Cost Management User Training Evaluation Methodology