Data/Backend Engineer (with Strong AI Expereince)

Hello, Title :

Software Engineer II (P3)

Location:

Redwood City, CA (Hybrid) About the Role As a Software Engineer II, you will be responsible for evolving and scaling the AI metrics and analytics ecosystem. You will take ownership of existing metrics pipelines stabilizing, extending, and operationalizing them while ensuring data quality, reliability, and usability. This role operates at the intersection of data engineering, platform engineering, and AI enablement , working closely with internal stakeholders and external vendors to deliver actionable insights and improve how AI impact is measured across the organization. Key Responsibilities Own and enhance AI metrics pipelines to improve scalability, reliability, and data quality Diagnose and resolve data pipeline issues, coordinating with internal teams and external vendors Extend pipelines to support new AI products, teams, and use cases Design and implement analytics solutions, including dashboards, reporting tools, and data access layers Partner with product, engineering, and AI teams to define and refine meaningful metrics Ensure data is accessible, accurate, and actionable for both technical and non-technical users Implement monitoring, alerting, and documentation for data systems Support additional AI teams with similar analytics and metrics needs Contribute to broader Production AI engineering initiatives over time Required Qualifications 3 5 years of professional software engineering experience Strong programming skills in Python, TypeScript, or similar languages Experience building, maintaining, or operating data pipelines or backend services Experience with APIs, data processing systems, and debugging production issues Familiarity with cloud platforms such as AWS or Google Cloud Platform and modern data tools Ability to independently own and deliver moderately scoped projects Strong communication and cross-functional collaboration skills Preferred Qualifications Experience with analytics and visualization tools (e.g., Tableau, Looker, Grafana) Familiarity with generative AI tools (ChatGPT, Claude, Gemini) and agentic workflows Experience working with third-party vendors or external platforms Knowledge of data modeling, ETL/ELT pipelines, and data quality best practices Experience building internal tools or developer platforms Familiarity with observability and monitoring systems What You ll Learn / Grow Into Design and scale metrics systems for AI platforms at enterprise level Apply AI/LLM systems in production and measure their real-world impact Partner with cross-functional teams to define and track AI success metrics Expand into broader AI platform and application development within Production AI