In this role, you will design, build and deliver AI-enabled full-stack solutions that support Contracting Operations and Revenue Management platforms within Amgen’s Global Commercial Operations and Corporate Functions Technology organization.

Your work will focus on integrating AI capabilities into practical full-stack solutions that reduce manual effort, improve data quality and increase process efficiency. You will partner with business, product and engineering teams to translate operational challenges into scalable technology solutions. This role is suited for senior engineers who are comfortable working across multiple systems, learning new domains over time and owning delivery from concept through implementation.

You will operate within a defined problem space, partnering with senior leaders to shape solution approaches and guide implementation across a small team. You will make design and implementation decisions within your scope, aligned to broader architectural direction. This is a hands-on engineering role with end-to-end ownership, requiring active solution design, coding, integration and delivery.

Roles & Responsibilities:

• Design, build and deliver scalable, enterprise-grade full-stack AI applications using React, Node.js, Python and Large Language Model APIs.
• Develop and manage robust integrations leveraging Databricks as the middleware platform, enabling seamless data and service orchestration.
• Translate business automation requirements into scalable technical designs and implement solutions across enterprise systems such as Salesforce CPQ/CLM, Anaplan and Model N.
• Contribute to AI-driven use cases, including workflow automation and lightweight assistant capabilities that enhance user productivity.
• Rapidly prototype and iterate AI automation solutions, emphasizing simplicity, maintainability and platform-first architecture.
• Collaborate closely with architecture, AI platform teams, and cross-functional partners to ensure alignment with enterprise standards and best practices.
• Provide technical leadership through design reviews, code reviews and hands-on implementation guidance to engineering teams.
• Decompose complex solutions into well-defined components, ensuring high quality through strong engineering practices and review processes.
• Collaborate with QA and DevOps teams to drive CI/CD pipeline enhancements.
  • Own end-to-end delivery of AI automation solutions from design through stabilization, driving measurable improvements in cycle time, data quality and operational efficiency.