Forward-Deployed AI Solutions Engineer

Mitra Data Semesta (MDS)

Jakarta Pusat

On-site

IDR 180,000,000 - 300,000,000

Full time

14 days+

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Job summary

Venus AI, the AI Deployment Division of PT Mitra Data Semesta (MDS), partners with Indonesian enterprises to embed AI in operations. You’ll sit with clients, diagnose problems they’ve misdiagnosed, and design the system with our founder.

This is a designing-and-building role where you’ll work on two to three engagements in parallel, decide when an agent is needed, define the ontology, and build with staged plans and invariant tests before shipping.

Qualifications

  • Shipped an LLM system that real users touched, can explain why it broke or behaved unexpectedly.
  • Proficient in Python for production systems, with handling of queues, databases, and APIs.
  • Excellent product sense: differentiate technically correct outputs from what a sales manager would send.
  • Fluent Bahasa Indonesia and precise technical English.
  • Willing to tell a client that their requested solution isn’t what they truly need; based in Jakarta or willing to relocate.

Responsibilities

  • Run discovery: read client artifacts and come back with a diagnosis that contradicts the brief.
  • Decide what shape the solution should take before assuming it’s an agent.
  • Design the ontology: entities, rules, and what the system must never decide alone.
  • Build through agentic engineering: staged build plans and invariant test suites.
  • Write the evals that decide whether we ship.
  • Stay with it after launch: monitor real outputs weekly with the client.

Skills

Shipped an LLM system
Production Python
APIs & queues
Product sense
Bahasa Indonesia + English

Job description

Venus AI, the AI Deployment Division of PT Mitra Data Semesta (MDS), partners with Indonesian enterprises to embed AI in operations. You’ll sit with clients, diagnose problems they’ve misdiagnosed, and design the system with our founder.

This is a designing-and-building role where you’ll work on two to three engagements in parallel, decide when an agent is needed, define the ontology, and build with staged plans and invariant tests before shipping.

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