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# Full-stack Developer

- **Company:** International Paper
- **Location:** Memphis, TN, United States
- **Experience:** Expert
- **Salary:** $83,000.0 - $121,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Data Analysis, Business Logic, Microsoft Azure, Business Systems, Software as a Service, Custom Software, Data Integration, Data Transformation, Data Mining, Decision Support Systems, Github, Design of User Interfaces, Human-Computer Interaction, Python (Programming Language), Machine Learning, Node.Js, Operational Data Store, Recommender Systems, Reliability Engineering, Software Engineering, SQL Databases, TypeScript, Data Ingestion, ReactJS, Backend, AngularJS, Information Technology, Data Analytics, Front End Software Development, Restful APIs, Software Version Control, Data Pipelines, Api Management, Web Api
- **Published:** October 3, 2026
- **Apply:** https://dejobs.org/x/x/AFB365A7A35047CAB1061EB551843808/job/

## About the Role

* Bachelor's Degree in Computer Science, Software Engineering, Data Science, Engineering, or related field + 2 years of relevant experience; equivalent Master's degree accepted; non-relevant bachelor's degree requires 5+ years of equivalent hands-on experience.
 * Hands-on experience developing:
 * REACT, Angular, JavaScript, Python, SQL, TypeScript, RESTful APIs, Node.js
 * Analytics applications, dashboards, and operational reporting solutions
 * API integrations, data pipelines, and automated workflows
 * Custom applications that solve manufacturing, operational, or business problems
 * User-friendly UI/UX design, including clean visual layout, intuitive navigation, error-proofing, and practical usability for business and manufacturing users
 * Experience working with:
 * SQL databases, APIs, process historians, manufacturing systems, and time-series data
 * Data transformation, validation, and business logic
 * Microsoft-based development environments and tools, preferably including Azure DevOps repositories, source control, and collaboration within a Microsoft enterprise ecosystem
 * End-to-end workflows (data ingestion * processing * analytics * user interface)
 * Demonstrated ability to:
 * Develop user-facing analytics tools and applications
 * Integrate applications with operational and business data sources
 * Build solutions that support manufacturing, reliability, quality, or operational improvement initiatives
 * Own projects from concept through deployment, * GitHub, portfolio, or equivalent examples of technical work; for hiring review purposes, submitted examples should not include AI-assisted builds.

## Description

* Internal interfaces with pre-approved software stack with contracted SaaS vendors
 * External vendor builds
 * Accelerate AI adoption and standardize scalable AI solutions across manufacturing and business functions
 * Develop analytics applications, dashboards, and operational reporting solutions used by manufacturing, reliability, quality, and engineering teams
 * Build integrations between operational data sources, business systems, and analytical applications
 * Support user-facing tools that enable data-driven decision making across mills and corporate functions

Integrate backend logic:

 * APIs
 * Data pipelines
 * ML outputs to UI
 * Process historian and manufacturing system data integrations and connections
 * Data transformation, validation, and business logic supporting analytical workflows
 * Predictive analytics and recommendation engines that support operational improvement initiatives

Additional General Responsibilities

 * Reduce engineering bottlenecks
 * Improve speed to value
 * Support end to end integration of development from data extraction to backend architecture/API endpoints to frontend development with REACT and Angular frameworks
 * Explore and implement advanced capabilities (agent automation, recommendations, closed-loop optimization)
 * Positions the team to scale AI/analytics capabilities as AI software stack matures rather than reacting later with limited capacity
 * Develop and maintain automated reporting, monitoring, and alerting solutions
 * Support collection, cleansing, transformation, and governance of manufacturing and operational data
 * Partner with operations, process engineers, reliability engineers, maintenance teams, and business stakeholders to identify and deliver analytics solutions
 * Apply statistical analysis, machine learning, and data science techniques to support process optimization, reliability improvement, quality enhancement, and operational performance initiatives
 * Evaluate and implement AI-enabled tools while validating outputs and ensuring responsible business use
 * Translate operational and business requirements into scalable analytical solutions
 * Identify opportunities to automate manual processes and improve existing workflows
 * Support deployment, testing, documentation, and continuous improvement of analytics solutions