Zealogics Inc

• Lead and develop the engineering team while strengthening technical capabilities across multiple customer organizations. • Identify, recruit, and deploy qualified engineering resources to meet customers' manpower and project requirements. • Prepare Statements of Work (SOW), quotations, and commercial proposals based on customer requirements. • Provide timely support for urgent customer issues, including emergency manpower allocation and resolution of technical or personnel-related challenges. • Evaluate and promote opportunities for Taiwan-based manufacturing and outsourcing partnerships. • Leverage strong hands-on experience in semiconductor equipment to understand customer challenges, provide practical solutions, and support technical decision-making. • Support customer performance evaluations of assigned engineers and drive continuous improvement based on customer feedback. • Resolve conflicts and communication issues between customers and their internal engineering teams. • Regularly report customer business status, manpower deployment, project progress, and business development updates to management. • Support business development activities and undertake additional assignments as required. • Hands-on experience in system/module assembly, integration, troubleshooting, and on-site technical support. • Solid understanding of assembly processes, system and hardware integration, testing, debugging, and manufacturing workflows within semiconductor equipment companies.

• Design and implement enterprise data architectures including Data Lakes, Data Warehouses, Data Fabric, and MDM solutions. • Build scalable data pipelines and data integration frameworks. • Define data governance, quality, lineage, and security standards. • Enable AI/ML initiatives through robust data engineering and architecture practices. • Collaborate with business and technology teams to develop data strategies and roadmaps. • Optimize data platforms for performance, scalability, and reliability.

• Participate in algorithm development for inspection and metrology • Collaborate with architects, designers, and engineers to develop robust computer vision modules • Work with Product Management to prioritize feature development and breakdown tasks • Drive infrastructure and architectural optimization solutions • Perform code reviews and ensure proper design and delivery • Assessment and improve algorithm performance • Software development based on product/project requirements. • Inspection flow and inspection module performance evaluation and optimization. • Software troubleshooting and bug fixing. • Cross-nation and cross-team communication to understand the tasks and ensure projects are on time and teamwork smoothly.

• Cooperating with software teams and maintaining the build scripts • Improving site reliability • Enforcing good software development practices using infrastructure as code (IAC) methodology • Site reliability/uptime management • CI/CD maintenance and automation of CI/CD processes • Security monitoring and patching • Downtime and patching communication with internal/external stakeholders • System upgrades • New tool implementation and onboarding • Other DevOps related issues included but not limited to above

• Ensure master data is AI‑ready, supporting machine learning, analytics, and Generative AI use cases. • Collaborate with Data Science and AI teams to: Define training‑data requirements, Prevent bias and duplication in AI inputs, Improve feature quality through high‑quality master data, Implement AI‑assisted data matching, classification, and enrichment where applicable. • Support explainability, lineage, and traceability requirements for AI and ML models. • Enable natural‑language and AI‑driven access to master data for analytics and decision support platforms. • Work closely with MDM platforms and tools. Define and oversee integration patterns between MDM, ERP, CRM, data platforms, and AI pipelines. • Collaborate with data engineering teams on cloud‑based data platforms, APIs, and automation workflows. • Ensure master data availability and consistency across operational, reporting, and AI systems. • Lead and mentor Master Data Stewards and Analysts. • Act as a key stakeholder in enterprise Data & AI initiatives. • Drive organizational adoption of data governance and AI‑driven data quality practices. Communicate MDM and AI value clearly to technical and non‑technical stakeholders.

Title: Platform System Specialist (GitHub Admin) Location: Remote Department: Audit Contracted Experienced Job Description: Platform System Specialist (GitHub Admin) Job Location: Remote Duration: 1 year+ GitHub Platform Administration - Administer and manage enterprise GitHub environments, repositories, organizations, teams, and access controls. - Configure and maintain GitHub Enterprise governance standards, branch protection rules, repository policies, and environment security settings. - Manage GitHub Environments, pull request approvals, status checks, and deployment workflows. - Support onboarding and enablement of development teams onto GitHub platforms. GitHub Advanced Security & Compliance - Implement and manage GitHub Advanced Security (GHAS) capabilities including: - Code scanning - Secret scanning - Dependency scanning - Security alerts and remediation workflows - Conduct security reviews and vulnerability analysis using Fortify and GitHub security tools. - Monitor GitHub Audit Logs and integrate security events with Splunk and Azure Monitor. - Ensure compliance with enterprise governance, audit, and regulatory requirements. Monitoring & Reporting - Develop dashboards and operational reports for: - Deployment frequency - Change tracking - Vulnerability remediation - Repository activity - Compliance metrics - Create GitHub Insights and reporting solutions for leadership and engineering teams. - Monitor platform reliability, workflow performance, and operational health. API & Platform Integration - Integrate GitHub platforms with Azure DevOps, ServiceNow, monitoring tools, and enterprise applications. - Automate work item synchronization, audit tracking, and deployment traceability. - Support API integrations and platform modernization initiatives. Collaboration & Support - Work closely with DevOps, engineering, security, infrastructure, and compliance teams to support enterprise delivery initiatives. - Troubleshoot GitHub workflow issues, deployment failures, and access-related incidents. - Provide guidance, documentation, and best practices for GitHub usage across teams. - Support Agile/Scrum delivery processes and continuous improvement initiatives. Required Skills & Qualifications Technical Skills Strong hands-on experience with: - GitHub Enterprise Administration - GitHub Actions - GitHub Advanced Security (GHAS) - Azure DevOps - Branch protection and repository governance - REST APIs and integrations - Splunk / Azure Monitor - Fortify

• Lead end-to-end design and development of the solution across Teams (frontend) and Azure (backend) • Develop Microsoft Teams applications using SPFx / React • Build and manage Azure Functions–based APIs and backend services • Implement integrations with Microsoft Graph API and SuccessFactors (GLMS) • Design and develop attendance tracking and completion logic • Ensure production readiness including performance, security, monitoring, and deployment • Drive Agile delivery across sprints and manage technical dependencies

• Perform end-to-end testing: Meeting setup → Attendance tracking → Completion calculation → GLMS sync • Validate API integrations and file-based workflows • Conduct UI testing across Teams app components • Validate data accuracy (attendance %, completion logic, reporting) • Execute regression and support automation initiatives

• Design, develop, and maintain complex, large-scale Python applications. • Write clean, efficient, reusable, and testable Python code following best practices. • Build and optimize backend services, APIs, and microservices. • Participate in system architecture design and technical decision-making. • Develop and integrate AI/ML-based features into applications (e.g., LLMs, NLP, data extraction, analytics). • Work with AI frameworks, models, and inference pipelines as part of production systems. • Optimize AI workflows for performance, accuracy, and scalability. • Design, implement, and optimize data models using PostgreSQL (or other relational databases) and MongoDB (and/or other NoSQL databases). • Handle large datasets efficiently with optimized queries and indexing strategies. • Ensure data integrity, performance tuning, and scalability. • Architect scalable, fault-tolerant, and secure systems. • Optimize system performance, memory usage, and latency. • Implement robust error handling, logging, and monitoring. • Collaborate with architects, product managers, data scientists, and DevOps teams. • Review code and mentor junior developers. • Contribute to technical documentation, design reviews, and best-practice standards. • Write and maintain unit tests, integration tests, and automated test suites. • Ensure high code quality and adherence to SDLC best practices. • Participate in CI/CD pipelines and deployment readiness.

• Design, develop, and maintain robust full stack applications using React (frontend) and Node.js/Express or similar (backend). • Architect and implement scalable RESTful APIs and ensure seamless integration between frontend and backend. • Follow and implement the MVC pattern to promote code clarity and maintainability. • Collaborate with AI/ML teams to integrate models and intelligent features into the product. • Write clean, maintainable, and testable code across the stack. • Participate in code reviews and contribute to the team’s technical direction. • Troubleshoot issues, optimize performance, and improve user experience. • Stay up-to-date with the latest industry trends and emerging technologies.