Zealogics Inc

DevOps Engineer

• 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

Senior DevOps Engineer – SRE

Data Scientist

• 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.

Master Data Manager – Data Governance, AI Enablement

Backend Engineer

• 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.

Senior Python Developer

QA Engineer

• 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

QA Engineer, Gen AI

Software Engineer

• 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

Lead Developer – Microsoft Teams, Azure Integration Platform

Full-stack Engineer

• 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.

AI Fullstack Developer

Systems Engineer

• 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.

Senior MES/EAP System Engineer

Data Analyst

• 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.