Senior AI Application Developer - Manufacturing

Country United States of America

State / County Various Locations

City Various Locations

Division EPD

Company EPD Division

Function Information Technology

Workplace Type On-Site

Position type Full Time

Opportunity

Location:

Los Angeles, CA or Seattle WA.

Travel:
Up to 30%

The Senior AI Application Developer is responsible for designing, developing, deploying, and sustaining AI-enabled applications and workflows that improve decision-making and operational performance across two manufacturing divisions. This role is first and foremost an application development position, with a strong emphasis on applied AI, data, and full-stack development. The developer will build production-quality solutions using the PCC data and AI ecosystem, including Databricks, Python-based application frameworks, APIs, AI models, agents, and modern web technologies.

Unlike a traditional centralized software development role, this position is expected to develop a strong understanding of the manufacturing environments it supports. The developer will spend time at manufacturing sites working directly with Operations, Supply Chain, Quality, Engineering, Continuous Improvement, and other functional teams to understand processes, identify opportunities, validate solutions, and ensure applications work in the real operating environment.

Travel of up to 30% is expected, particularly to build familiarity with manufacturing sites, processes, data, users, and business challenges across both divisions. The successful candidate will combine strong software engineering capabilities with curiosity about manufacturing and a practical, continuous-improvement mindset.

• Design, develop, test, deploy, and maintain AI-enabled applications and workflows supporting manufacturing and business operations.
• Build full-stack applications using Python, JavaScript, and frameworks such as Dash, Streamlit, React, Flask, or similar technologies.
• Develop applications using Databricks Apps and the broader enterprise data platform.
• Build AI agents and AI-assisted workflows that automate analysis, improve access to information, and support operational decision-making.
• Integrate REST APIs, model endpoints, enterprise data services, large language models, and other AI capabilities into production applications.
• Develop reusable application components, services, patterns, and templates that accelerate development across multiple sites and use cases.
• Write maintainable, documented, production-quality code using Git, testing, code review, and CI/CD practices.
• Monitor and improve application reliability, usability, performance, and maintainability.

• Work directly with manufacturing sites to understand business processes, operating challenges, data sources, and user requirements.
• Spend time on the shop floor with operators, supervisors, engineers, planners, quality personnel, and site leadership to understand how processes actually operate.
• Translate manufacturing and business problems into well-defined application and AI requirements.
• Identify opportunities where AI, analytics, automation, or improved access to data can materially improve safety, quality, delivery, cost, inventory, productivity, or decision-making.
• Validate application outputs against actual operating conditions rather than relying exclusively on system data or stated requirements.
• Participate in pilots, user testing, deployment, training, and adoption of new applications.

• Own solutions through the complete application lifecycle, including discovery, requirements, architecture, development, testing, deployment, adoption, enhancement, and sustainment.
• Work with business stakeholders to define measurable success criteria before development begins.
• Balance rapid prototyping with appropriate production engineering practices based on the scale and criticality of the application.
• Develop intuitive tools that fit naturally into existing business and manufacturing workflows.
• Gather user feedback and translate it into prioritized application enhancements.
• Maintain appropriate application documentation, data definitions, testing, controls, and support processes.

• Work with manufacturing, ERP, supply chain, quality, and operational data to create AI-enabled applications and decision-support tools.
• Collaborate with data engineering, data…