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Salary
$45k – $58k per year (gross)
Location
In office (Singapore)
Seniority
Middle · 3+ years exp
Employment
Full-Time

First seen by Alion on Sep 25, 2026.

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Mindteck delivers IT services and product engineering across AI, IoT, and embedded systems, helping global enterprises drive digital transformation.

Singaporean Only

Job Title: Technical Engineer – QA Automation

Job Overview

We are seeking a skilled and technically versatile Technical Engineer to support Quality Assurance (QA) and Solution Architecture (SA) responsibilities within a learning technology project deployed at the customer’s site. The successful candidate will work closely with the operations, delivery, and customer teams to ensure the quality, stability, and architectural integrity of the platform and its integrations.

The role demands strong hands-on technical expertise, an eye for quality engineering, and the ability to design and review solution components in a structured, customer-facing environment. Familiarity with Artificial Intelligence (AI) technologies is a key prerequisite for this role.

Key Responsibilities

Quality Assurance (QA)

• Design, develop, and execute test plans, test cases, and test scripts for functional, regression, integration, and performance testing

• Perform system and user acceptance testing (UAT) in coordination with customer stakeholders and end users

• Identify, document, and track defects through to resolution using standard issue-tracking tools

• Validate system enhancements, patches, and releases prior to production deployment

• Maintain QA documentation, test artefacts, and quality metrics

• Drive continuous improvement in testing processes, tooling, and test coverage

Solution Architecture (SA)

• Support the design and review of solution components, integrations, and system architectures for the learning technology platform

• Provide technical guidance on platform configurations, API integrations, and infrastructure alignment

• Analyse technical requirements and translate them into clear architectural specifications and design documentation

• Collaborate with delivery teams, infrastructure teams, and vendors to validate technical solutions

• Ensure architectural decisions comply with organisational standards, security policies, and governance requirements

• Support technical onboarding, handover, and knowledge transfer activities

AI & Emerging Technologies

• Apply knowledge of AI and machine learning concepts to evaluate, support, or enhance platform capabilities

• Assess and advise on AI-powered features, tools, and integrations within the learning technology ecosystem

• Stay current with developments in AI technologies relevant to the platform and propose practical applications

Stakeholder & Cross-Functional Collaboration

• Liaise with customer stakeholders, project managers, and operations teams on technical quality and solution matters

• Provide technical input during design reviews, change advisory processes, and operational readiness activities

• Prepare and present technical reports, architecture diagrams, and QA summaries for project and management review

Qualifications & Experience

• Bachelor’s degree in Information Technology, Computer Science, Software Engineering, or a related discipline

• At least 3–5 years of relevant experience in QA engineering, solution architecture, or a combined technical role

• Hands-on experience with test automation frameworks and testing tools (e.g. Selenium, Postman, JMeter, or equivalent)

• Experience with enterprise digital platforms, cloud-based systems, or Learning Management Systems (LMS)

• Demonstrated experience in solution design, integration architecture, or technical documentation

• Familiarity with AI technologies, machine learning platforms, or AI-enabled applications

• Experience working in structured project delivery and governance environments

Certifications

Mandatory

• ITIL Foundation Certification (or equivalent IT Service Management certification)

• Relevant AI certification or demonstrated AI experience (e.g. Microsoft AI Fundamentals – AI-900, Google Cloud AI, AWS AI Practitioner, or equivalent)

Preferred / Good-to-Have

• Microsoft Azure certification (e.g. Azure Fundamentals, Azure Developer, Azure Solutions Architect)

• ISTQB Foundation or Advanced Level certification in software testing

• Project management certifications such as PMP, PRINCE2, Agile, or Scrum

• Learning Management System (LMS) platform certifications

• Certified Solutions Architect credentials (e.g. AWS, Azure, GCP)

Competencies & Skills

• Strong technical proficiency in QA methodologies, test design, and defect management

• Sound understanding of solution architecture principles, integration patterns, and system design

• Working knowledge of AI/ML concepts and their application in enterprise or learning technology environments

• Good analytical, problem-solving, and critical-thinking capabilities

• Strong communication skills with the ability to articulate technical concepts to non-technical stakeholders

• Detail-oriented with a quality-first mindset

• Ability to manage multiple tasks and priorities in a fast-paced, customer-facing environment

• Proficiency in preparing technical documentation, architecture diagrams, and reports

Preferred Attributes

• Experience in public sector, education, or large-scale digital transformation environments

• Familiarity with ticketing and service management platforms (e.g. ServiceNow, Jira)

• Understanding of DevOps practices, CI/CD pipelines, and release management

• Experience with API management, middleware, or enterprise integration platforms

• Understanding of governance, compliance, and audit processes

• Ability to work both independently and collaboratively within cross-functional teams

Skills

Ai, Test Automation Framework, Learning Platform, Quality Assurance & Testing, Quality Assurance, Continuous Process Improvement, Artificial Intelligence, Technology-Enabled Learning Delivery, Qa Systems, Test Automation, Defect Tracking, Solution Architecture, Functional Testing, Learning Management Systems, Qa Testing, E-Learning Management System, Testing

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