AI & Data Product Builder — Ship Trusted AI

Mekari; Jakarta Pusat; On-site; IDR 240,000,000 - 420,000,000; Full time

Job summary

Mekari, Indonesia's leading SaaS company, is seeking an AI/Data Builder to own AI/ML/LLM data products and guardrails. You will ship end-to-end AI/data capabilities, measure quality, and iteratively improve prompts, models, and pipelines in production.

The role emphasizes probabilistic behavior, data quality, and user trust, with close collaboration with Platform and Product teams. Join a fast-growing environment where you will stay close to users, define success metrics, design evaluation

Qualifications

• 2-3+ years in full-stack engineering or applied software development using AI/data use cases.

Responsibilities

• Own AI/data behavior quality and guardrails in production.
• Ship AI services, ML models, LLM workflows, and data pipelines as product capabilities.
• Define prompts, retrieval logic, model configs, and data transformations.
• Test behavior with eval sets, golden datasets, and human review.
• Manage risk: grounding, hallucination, bias, privacy, latency, cost, drift.
• Release with guardrails, monitoring, and human-in-the-loop controls.
• Iterate prompts, models, and pipelines based on usage data.
• Collaborate with Platform Builders and Product Builders to ensure release readiness.

Skills

AI/Data systems

Full-stack engineering

Prompt engineering

Data quality

Model evaluation

RAG systems

Pipeline design

Tools

Python

ML frameworks

LLM tooling

Retrieval systems

Job description

Mekari, Indonesia's leading SaaS company, is seeking an AI/Data Builder to own AI/ML/LLM data products and guardrails. You will ship end-to-end AI/data capabilities, measure quality, and iteratively improve prompts, models, and pipelines in production.

The role emphasizes probabilistic behavior, data quality, and user trust, with close collaboration with Platform and Product teams. Join a fast-growing environment where you will stay close to users, define success metrics, design evaluation