Senior AI Engineer: Build Auditable Knowledge Base

Qonnectiq; Jakarta Barat; On-site; IDR 300,000,000 - 600,000,000; Full time

Job summary

Qonnectiq in Jakarta Barat is seeking an Artificial Intelligence Engineer to turn a large document archive into a structured knowledge base with auditable provenance. You will design the database schema, implement versioning, and ensure every figure traces back to its source while building PDFs parsing pipelines and OCR for complex layouts.

The role emphasizes data correctness (60% data engineering, 30% AI/search, 10% testing) and requires strong SQL, document parsing experience, and the ability

Qualifications

• Strong experience designing relational database schemas with versioning of historical data.
• 5+ years in AI/ML engineering and document parsing from PDFs or semi-structured formats.
• Experience with retrieval-augmented generation and LLM-based applications.
• Ability to compare in-house vs commercial AI providers and justify choices.
• Excellent SQL and familiarity with similarity search databases.
• Ability to explain technical decisions to non-engineers and domain experts.
• Solid technical English; documents are English and dense with abbreviations.

Responsibilities

• Design and own the database schema that acts as the source of truth.
• Implement versioning and as-of-date logic for historical values.
• Ensure provenance: source document, location, extraction method, and confidence.
• Build pipelines to parse PDFs with complex layouts and OCR for scanned docs.
• Extract structured entities like operating parameters and instrument readings.
• Develop entity resolution to attach documents to correct assets.
• Normalise units and measurement reference systems across sources.
• Create a validation layer to flag contradictions between sources.
• Deduplicate overlapping work periods and publish data quality reports.
• Model relationships between assets and compute contextual links.
• Build search that prioritizes structured fields then semantic meaning.
• Define how the draft document is assembled from retrieved data.
• Assess use of commercial AI providers vs in-house models and keep layer replaceable.
• Build test sets and repeatable checks to catch regressions before release.
• Ship with safeguards, monitoring, and human review for feedback loops.

Skills

Relational DB Design

Data Versioning

SQL Expert

Provenance Tracking

RAG

Document Parsing

Model Deployment

Similarity Search

Explainability

Non-engineer Communication

Education

Bachelor's degree in Computer Science

Tools

PostgreSQL

Elasticsearch

Python

OCR

Graph DB

Job description

Qonnectiq in Jakarta Barat is seeking an Artificial Intelligence Engineer to turn a large document archive into a structured knowledge base with auditable provenance. You will design the database schema, implement versioning, and ensure every figure traces back to its source while building PDFs parsing pipelines and OCR for complex layouts.

The role emphasizes data correctness (60% data engineering, 30% AI/search, 10% testing) and requires strong SQL, document parsing experience, and the ability