Graduate Solution Consultant, Technical

AI Digital Foundry; Tangerang; Hybrid; IDR 167,400,000 - 334,800,000; Full time

Job summary

PT Artifisial Indonesia Digital Fabrikasi in Batam is seeking a Technical Solution Consultant to translate customer requirements into AI inference architectures and deliver end-to-end proofs of concept. You will spend most of your time coding, drafting architectures, and collaborating with customer engineering or project teams.

You will own the technical agenda from first conversation to production cutover, run technical discovery, design reference architectures, build demos, and support

Qualifications

• Graduate entry level or early career experience in solutions engineering, pre-sales engineering, platform engineering or applied AI/ML engineering.
• Strong Python and production-grade integration code.
• Hands-on experience with LLM APIs and LangChain or LlamaIndex.
• Working understanding of inference mechanics: tokenisation, context windows, batching, streaming, quantisation and their effect on cost and latency.
• Practical knowledge of cloud and container fundamentals, networking, and API authentication and security patterns.
• Excellent communication in English and Bahasa Indonesia.
• Exposure to fine tuning, adapter training or model distillation workflows.
• Familiarity with data residency and sovereignty requirements in public sector or regulated industry contexts.
• Experience working with GPU or accelerator infrastructure and understanding of where throughput ceilings come from.

Responsibilities

• Run technical discovery with prospective customers. Establish workload profile, latency and throughput targets, data handling constraints and integration surface.
• Design reference architectures using the OpenAI-compatible inference API, including model selection, routing, context handling, embeddings and retrieval patterns.
• Build proofs of concept and working demonstrations. Write the integration code.
• Lead evaluation and benchmarking exercises. Define the test set with the customer, run the comparison, and present results honestly, including where the platform is not the right fit.
• Support migration from existing providers, including SDK swap, prompt and parameter translation, and regression testing against the customer’s own evaluation set.
• Diagnose and elevate platform issues during evaluation and early production. Own the technical thread until resolution.
• Feed structured product and capability gaps back to the vendor AI engineering team with reproducible detail.
• Contribute reusable assets: integration templates, evaluation harnesses, architecture patterns, internal and partner enablement material.

Skills

Python

LLM APIs

LangChain

Vector stores

Cloud fundamentals

Containerization

English communication

Bahasa Indonesia communication

GPU/accelerator infra

Pre-sales engineering

Tools

OpenAI API

LangChain

LlamaIndex

Evaluation tooling

Job description

AI Infrastructure and Applied Engineering Program

Reports to

Location

Batam, hybrid

Type

Full time, 6 month contract

Focus

Purpose of the role

The Technical Solution Consultant is the engineering voice in the room. You take a customer requirement, translate it into a working inference architecture on AI platforms, and prove it end to end. You spend most of your week in code, in a terminal, or in a whiteboard session with a customer engineering or project team. You own the technical agenda from first conversation to production cutover.

Key responsibilities

• Run technical discovery with prospective customers. Establish the workload profile, latency and throughput targets, data handling constraints and integration surface.
• Design reference architectures using the OpenAI-compatible inference API, including model selection, routing, context handling, embeddings and retrieval patterns.
• Build proofs of concept and working demonstrations. Write the integration code.
• Lead evaluation and benchmarking exercises. Define the test set with the customer, run the comparison, and present results honestly, including where the platform is not the right fit.
• Support migration from existing providers, including SDK swap, prompt and parameter translation, and regression testing against the customer’s own evaluation set.
• Diagnose and elevate platform issues during evaluation and early production. Own the technical thread until resolution.
• Feed structured product and capability gaps back to the vendor AI engineering team with reproducible detail.
• Contribute reusable assets: integration templates, evaluation harnesses, architecture patterns, internal and partner enablement material.

Required experience

• Graduate entry level or early career experience in solutions engineering, pre-sales engineering, platform engineering or applied AI/ML engineering.
• Strong Python. Comfortable building and debugging production quality integration code.
• Hands-on experience with LLM APIs and the surrounding ecosystem, for example OpenAI-compatible endpoints, LangChain or LlamaIndex, vector stores, and evaluation tooling.
• Working understanding of inference mechanics: tokenisation, context windows, batching, streaming, quantisation and their effect on cost and latency.
• Practical knowledge of cloud and container fundamentals, networking, and API authentication and security patterns.
• Excellent communication in English and Bahasa Indonesia.
• Exposure to fine tuning, adapter training or model distillation workflows.
• Familiarity with data residency and sovereignty requirements in public sector or regulated industry contexts.
• Experience working with GPU or accelerator infrastructure and understanding of where throughput ceilings come from.

What success looks like at six months

• Running technical discovery and proof of concept work independently across concurrent opportunities.
• Recognised by vendor, customer and project engineering teams as a credible technical counterpart rather than a vendor representative.
• A library of reusable integration and evaluation assets that shortens the next engagement.

These two roles are designed to work as a pair. The technical consultant proves it can be built. The functional consultant proves it is worth building and makes sure it is used.