Zealogics Inc

• 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.

• Lead end-to-end factory integration initiatives, from design through deployment and optimization • Drive connectivity of manufacturing tools to enterprise systems such as MES, EAP, RMS, RTD, SPC, and FDC • Define architecture and integration strategies for smart factory solutions • Work closely with semiconductor equipment, automation systems, and software platforms • Enable seamless communication using industry protocols (e.g., SECS/GEM, EAP) • Design and implement MES/EAP-related software solutions, including automation frameworks and integration components for semiconductor manufacturing systems, and equipment automation validation • Develop and support EAP driver automation, SECS/GEM communication flows, equipment interfaces, and manufacturing data exchange • Collaborate with cross-functional teams, including process, equipment, IT, and operations • Support deployment of factory automation, data collection, and analytics solutions • Provide technical leadership, troubleshooting, and continuous improvement initiatives • Organize meetings concerning all phases of product & project lifecycle (requirement collection, specification, development and testing, delivery, and sign-off). • Determine solutions for customer requirements through the application of MES. This includes analyzing and understanding customer manufacturing issues and requirements; understanding the customer environment and documenting its processes and procedures; mapping these processes and procedures onto CIM components; and interfacing with software engineers on MES application functionality and operation. It also includes determining the requirements for functionality beyond the standard product offering. • Keep up-to-date on new technologies and new products.

• Analyze large and complex datasets to identify trends, patterns, and correlations for business decision-making. • Develop and maintain dashboards and reports using tools such as Power BI, Tableau, or similar platforms. • Write efficient Python scripts for data cleaning, transformation, and correlation analysis. • Design and implement robust data models (conceptual, logical, and physical) by understanding various data inputs from different data sources. • Work with manufacturing datasets (production, Factories, Product Lines, Certifications, Qualifications, Sales, quality metrics) to improve operational efficiency. • Collaborate with global stakeholders (Europe & US) to gather requirements and deliver insights. • Ensure data quality, integrity, and governance across multiple data sources. • Adhere to data privacy, security, and compliance standards, especially for European data. • Support and optimize ETL processes and data pipelines.

• System Architecture & C# Core Design and build the core automation engine using C# / .NET. • Ensure the code is clean, scalable, and follows modern design patterns (Solid, Clean Architecture). • Solve complex technical challenges, such as compiling code at runtime or handling Windows UI interactions. • AI Integration (Real-world Application) Integrate LLMs (OpenAI, Azure, etc.) into the software workflow. • Design the logic for how the system interacts with AI—focusing on prompt structure, context management, and error handling (Self-healing). • Bridge the gap between "Generative AI" and "Reliable Software Execution." • Leadership & Communication Mentor & Guide: Help other engineers grow. Conduct code reviews and set engineering standards. • Bridge the Gap: Translate technical architecture into clear explanations for PMs and stakeholders. • Collaborate: Work with a mindset of "we" not "I". You are a partner in product decisions.

• System Architecture & C#: Design and build the core automation engine using C# / .NET. • AI Integration: Integrate LLMs (OpenAI, Azure, etc.) into the software workflow. • Leadership & Communication: Mentor and guide other engineers, setting standards, and collaborating.