Senior Software Engineer, Full Stack — Decision Intelligence

Career Category Engineering Job Description Senior Software Engineer, Full Stack — Decision Intelligence ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. The opportunity Amgen’s AI & Data Science team is building decision-intelligence products that help teams make faster, more defensible decisions under uncertainty. We are seeking a Senior Software Engineer, Decision Intelligence to join the Forecasting & Decision Intelligence team, within the AI & Data organization. This role will develop cutting edge scenario-planning capabilities, while creating reusable foundations for forecasting, simulation, optimization, and AI-assisted decision products across the enterprise. We are seeking a Full-Stack Engineer who can own meaningful product experiences end-to-end. You will build the interfaces people use to configure, launch, monitor, compare, and understand complex scenarios, as well as the APIs, data integrations, and execution services that make those experiences trustworthy. What you will do Design, build, deploy, and operate end-to-end decision-support products across frontend, backend, data, and workflow layers. Create intuitive planner experiences for configuring scenarios, managing assumptions, launching and monitoring, comparing outcomes, and understanding uncertainty and trade-offs. Build responsive, accessible React/TypeScript user interfaces and reusable frontend components for scenario setup, results visualization, and decision workflows. Design and implement production APIs, backend services, data integrations, and execution workflows for forecasting, simulation, optimization, and AI-assisted decision products. Work closely with product managers, planners, data scientists, and adjacent engineering teams to translate ambiguous business needs into simple, valuable releases. Lead substantial workstreams independently, provide thoughtful code reviews, and mentor developing engineers. Basic qualifications Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience. 10+ years of professional software-engineering experience, including ownership of complex production applications or major end-to-end capabilities. Strong full-stack engineering experience, including modern frontend development with React and TypeScript and backend API development with Python or another modern server-side language. Experience designing usable, data-rich web applications in partnership with product, design, and business stakeholders. Experience with relational SQL and data-intensive applications, including integration with warehouse, lakehouse, or operational data systems. Experience with asynchronous processing, queues, workflow engines, or resilient patterns for long-running workloads. Experience with cloud deployment, containers, CI/CD, automated testing, and production troubleshooting. Demonstrated commitment to code quality, accessibility, observability, documentation, and operational ownership. Preferred qualifications Experience with FastAPI, Databricks, Spark, Kubernetes, modular frontend architectures, or comparable technologies. Experience building interactive visualizations and comparison workflows for analytical, operational, financial, or planning users. Experience embedding statistical models, optimization engines, simulation, or machine-learning capabilities into production applications. Experience with API and data-contract versioning, enterprise identity and access management, and secure integrations. Experience in supply chain, manufacturing, healthcare, finance, or another complex operational domain. Familiarity with AI-assisted product experiences and appropriate grounding, evaluation, and human-review controls.

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