About the role
Requirements:
- Bachelor's degree in Computer Science, Software Engineering, Statistics, or a related field with 7-10 years of relevant professional experience.
- Strong production experience with Python and JavaScript/TypeScript across backend and frontend.
- Hands-on experience with modern frontend frameworks (such as Next.js or React) and backend API development.
- Production experience with cloud platforms (AWS preferred; Azure or GCP also valued), including infrastructure-as-code tools (such as CloudFormation or Terraform).
- Working knowledge of multiple database paradigms, including relational databases (such as PostgreSQL), document databases, and key-value stores (such as Redis).
- Experience with CI/CD pipelines (such as GitHub Actions) and a strong understanding of path-to-production practices.
- Demonstrable fluency with AI coding tools (such as Claude Code, Cursor, GitHub Copilot, or similar) and experience building agentic engineering workflows.
- Hands-on experience building production generative AI applications (LLM integrations, vector databases, RAG systems) is essential.
- Experience with data analysis, statistical modeling, or machine learning in a professional context is required. This could include exploratory data analysis, building regression or classification models, A/B test design, or integrating ML predictions into software products.
- Familiarity with data science tooling (such as pandas, scikit-learn, or equivalent) and comfort working in Jupyter notebooks or similar environments.
- Experience navigating ambiguous problem spaces, working directly with business stakeholders and end users, and shipping working solutions rapidly is strongly valued.
- Experience in an embedded, forward-deployed, or consulting-style engineering model is a strong plus.