AI & Automation Solutions Engineer

Key Responsibilities:

• Design, build, and maintain end-to-end data pipelines — from ingestion and transformation through to dashboards and applications consumed by end users — with a strong focus on solving the underlying business problem, not just delivering technical output.

• Develop and maintain BI dashboards and reports used by clinical, operational, and management stakeholders, ensuring metrics are accurate, well-defined, and actionable.

• Build and maintain full-stack internal applications from initial scoping through production deployment.

• Manage frequent deployments across multiple systems; ensure every system shipped is maintainable, well-documented, and traceable so issues can be diagnosed and ownership can be transferred.

• Ensure data traceability across all pipelines and reports — every number delivered to a stakeholder can be traced back to its source, transformation logic, and assumptions.

• Establish and follow engineering practices including version control (Git), CI/CD, and structured logging to keep a solo-operated system landscape reliable and auditable.

• Stay current and able to build developments integrated with AI/LLM models with tooling, and evaluate where new model capabilities can be applied to hospital data and automation use cases.

• Work directly with non-technical stakeholders to translate vague business questions into concrete data or application requirements, and communicate results in plain language.

Qualifications:

• Bachelor's degree in Computer Science / Information Technology / others related major

• Proficiency in SQL on production datasets, and in Python for data processing and pipeline development. (Familiar with PostgreSQL & MongoDB )

• Hands-on experience with at least one BI tool (Power BI, Tableau, or Metabase) delivering dashboards used in production by business stakeholders.

• Full-stack development experience, including version control workflows and CI/CD pipelines. ( Preferred experiences with Next.js, React, Go, FastAPI )

• Proven ability to operate as an engineer: scoping, building, deploying, and maintaining systems end-to-end without a supporting team, and prioritizing across multiple concurrent requests.

• An end-to-end pipeline mindset. Thinks from data sources all the way to the end user. Deep specialization is less important than the ability to ship working, maintainable solutions.

• Strong understanding of data traceability and system maintainability; comfortable being accountable for many deployed systems and able to keep them documented, monitored, and debuggable.

• Awareness of the current AI/LLM model landscape and its practical applications, with the judgment to know when (and when not) to apply them.

• Strong communication and stakeholder management skills, with the ability to work effectively in both Bahasa Indonesia and English across technical and business teams.

• Understanding of data sensitivity and access control practices, particularly in a healthcare or regulated-data environment (preferred: exposure to hospital information systems, HL7/FHIR, or BPJS data).