Software Engineer, Full Stack — Decision Intelligence

What you will do

• · Develop intuitive planner experiences for configuring scenarios, managing assumptions, monitoring runs, 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.
• · Develop 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 business needs into clear, valuable product increments.
• · Participate actively in code reviews, technical design discussions, and continuous improvement of engineering practices.
• Basic qualifications
• · Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
• · 5+ years of professional software-engineering experience building and supporting production applications.
• · 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 building 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.
• · Familiarity with asynchronous processing, queues, workflow engines, or similar patterns for long-running workloads.
• · Experience with cloud deployment, containers, CI/CD, automated testing, and production troubleshooting.
• · Commitment to code quality, accessibility, documentation, observability, 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.