AI & Data Engineer

SINGAPORE AMERICAN SCHOOL LIMITED; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A prominent international school in Singapore seeks a skilled professional for AI & Data Product Development. Responsibilities include designing advanced analytics systems, maintaining ETL pipelines, and ensuring secure AI practices. Candidates must hold a Bachelor’s degree in Computer Science or a related field and have proven experience in delivering AI systems. Strong communication skills are essential for translating technical concepts into actionable insights for non-technical partners. This role provides an opportunity to innovate in educational technology and data management.

Qualifications

• Bachelor's degree in relevant field is required.
• Proven experience in delivering production-grade AI systems required.
• Strong communication skills for technical translation are essential.

Responsibilities

• Design and deploy advanced analytics and machine learning models.
• Create and maintain automated ETL pipelines.
• Work closely with educational teams to translate technical solutions.
• Ensure AI practices meet ethical guidelines.

Skills

Python

JavaScript/TypeScript

Modern AI/ML frameworks

CI/CD pipelines

Cloud platforms

Docker/Kubernetes

Data governance

API development (REST/GraphQL)

Education

Bachelor’s Degree in Computer Science related field

Tools

GCP

AWS

Azure

FAISS/Pinecone

BigQuery

Looker Studio

Job description

Position Responsibilities

The specific roles and responsibilities are subject to change and evolve and may include but not be limited to any of the following areas:

AI & Data Product Development

• Design, build, and deploy advanced analytics and machine learning models aligned to SAS strategic priorities, including decision-support systems, workflow automation, recommender systems, and advanced data visualizations that improve teaching, learning, and operations.
• Lead development of AI copilots, agentic workflows, and RAG-based tools that help staff and educators interrogate information, improve productivity, and make evidence-informed decisions.
• Build evaluation, observability, and monitoring pipelines to ensure AI models remain accurate, safe, fair, and aligned with SAS policy and ethical guidelines.

Enterprise Data Architecture

• Create and maintain a highly automated ETL pipeline ecosystem that integrates all major school systems (SIS/LMS, assessment platforms, HR/Finance, operations systems, and third-party tools).
• Architect and optimize the SAS data lake with strong data models, lineage, and governance to support real‑time analytics and future AI integrations.
• Partner with Data Governance to ensure data quality, documentation, and long‑term maintainability of the school’s data infrastructure.

Governance, Safety & Security-by-Design

• Embed ethical, secure, and privacy-preserving AI practices across all engineering work, including: data minimization, anonymization, PII protection, guardrails, and secure access controls.
• Implement robust evaluation frameworks for safety, bias detection, and responsible use of generative and predictive systems.
• Ensure all systems and integrations meet SAS policies, regulatory requirements, and industry best practices for responsible innovation.

Cross-Functional Collaboration

• Work closely with the Educational Technology team to translate instructional problems into technical solutions that support assessment, personalization, student progress insights, and instructional planning.
• Collaborate with IT Operations to ensure infrastructure, deployment, and security models align with scalable cloud-first practices.
• Engage with external vendors, research partners, and EdTech organisations to benchmark SAS against emerging trends and inform future design.

Other Responsibilities

• Participate in professional learning opportunities, staying abreast of trends in AI and emerging technologies and their application in education.
• Complete other duties as assigned by the Technology Leadership Team.

Position Requirements & Qualifications

Required Education & Background

• Bachelor’s Degree in Computer Science, Mathematics, Software Engineering, Computer Engineering, or related field.
• Proven track record delivering production‑grade AI systems, including generative AI, RAG, or agentic workflows, from discovery through deployment and ongoing monitoring.
• Strong English communication skills with the ability to translate technical complexity into clear, actionable insights for non‑technical partners.

Required Technical Experience

• Programming & Frameworks: Python; JavaScript/TypeScript; modern AI/ML frameworks (e.g., LangChain/LangGraph); API development (REST/GraphQL); microservices and serverless patterns.
• AI/ML & Data Engineering: LLM tooling (prompting, RAG, safety/guardrails), vector stores (e.g., FAISS/Pinecone), data warehouses (e.g., BigQuery), dashboarding (Looker Studio), feature stores, and automated data pipelines.
• Cloud & Infrastructure: Cloud platforms (GCP/AWS/Azure), containerization (Docker/Kubernetes), CI/CD pipelines, observability, and secure, cost‑efficient deployments.
• Systems Integration: Experience integrating enterprise systems, ideally SIS/LMS, assessment platforms, authentication/SSO using secure APIs, webhooks, and data contracts.

Preferred

• Advanced degree in a relevant field
• Prior work in EdTech, K–12, higher education, or social‑impact contexts, especially building tools that improve instructional time, assessment, student support, or school operations.
• Background working with UX/UI designers to create educator‑friendly products with high adoption and usability.
• Familiarity with data governance, AI policy, digital citizenship, or responsible innovation frameworks.
• Knowledge of multi‑modal AI, simulation environments, agentic orchestration, or frontier model evaluation practices.