AI Engineer

McEasy; Indonesia; On-site; IDR 180,000,000 - 300,000,000; Full time

Job summary

McEasy is seeking an AI Engineer to turn 8+ years of logistics and IoT data into real, customer-facing intelligence. This role focuses on solving business problems using data, simple logic, and AI tools — not on building complex AI models.

You will work closely with leadership to translate ideas into features, build anomaly detection, insights, and benchmarking systems, and deliver outputs that customers can act on immediately. Collaboration with data, software, and product teams is essential.

Qualifications

• Proven backend development experience with Python, Node.js, or similar.
• Strong SQL and data manipulation skills for real-world datasets.
• Experience translating business problems into technical solutions.
• Track record of building and shipping features (not just prototypes).
• Experience working with messy real-world data and deriving actionable insights.

Responsibilities

• Build data-driven features such as anomaly detection and weekly insights.
• Design simple rules, thresholds, and statistical methods for useful outputs.
• Develop and ship backend services to process data and generate insights.
• Use AI tools to summarize insights, explanations, and improve user experience.

Skills

Backend development

SQL

Data manipulation

Translate business problems

Shipping features

Job description

We are looking for an AI Engineer to turn 8+ years of logistics and IoT data into real, customer-facing intelligence.

This role is not about building complex AI models.

It is about solving real business problems using data, simple logic, and AI tools — and shipping fast.

You will work closely with leadership to:

• translate ideas into working features
• build anomaly detection, insights, and benchmarking systems
• deliver outputs that customers can act on immediately

What will you do?

1. Build Data-Driven Features

• Develop features such as anomaly detection (fuel, trips, driver behavior), fleet benchmarking, and automated weekly insights.
• Turn raw data into clear, actionable outputs.

2. Design Simple, Effective Logic

• Start with rules, thresholds, and statistical methods.
• Avoid overengineering — focus on usefulness over complexity.

3. Develop and Ship Fast

• Build backend services to process data (batch or near real-time), detect anomalies or patterns, and generate insights.
• Deliver MVPs quickly and iterate based on feedback.

4. Use AI Tools Practically

• Use LLMs (e.g., Claude, GPT) for summarizing insights, generating explanations, and enhancing the user experience.
• Combine AI with structured logic and data.
• Work with Data Engineers to access clean datasets.
• Work with Software Engineers to integrate solutions into the product.
• Work with Product/Leadership teams to refine use cases.

Qualifications

Must-Have

• Strong backend development skills (Python, Node.js, or similar)
• Solid SQL and data manipulation experience
• Experience working with real-world, messy datasets
• Ability to translate business problems into technical solutions
• Track record of building and shipping features (not just prototypes)

Nice-to-Have

• Experience with: anomaly detection or time-series data, logistics / IoT datasets
• Familiarity with: LLM APIs (OpenAI, Claude, etc.), basic statistical methods