Product Software Engineer I

Job Title

Sitting inside the Product and Engineering team, the Client-Data team bridges data requirements between our front-end applications and engineering services. Our work spans software engineering, machine learning, and data science at scale — from platform health monitoring and performance tracking for new releases to synchronizing instrumentation, metrics, and data-related decisions across platforms. Day to day, our work directly impacts the business through application engagement monitoring, anomaly detection, and more.

The team leverages AI-powered tools and generative AI to accelerate development, automate data quality checks, and surface actionable insights from telemetry data at scale. This includes integrating AI/ML products — intelligent anomaly detection, AI-assisted code generation, and natural language interfaces for data exploration — into both internal tooling and consumer-facing experiences. Team members are expected to stay current with the evolving AI landscape and identify opportunities to apply foundation models, RAG, and other AI-driven approaches to improve observability, streamline instrumentation pipelines, and drive smarter, data-informed decision-making.

Responsibilities and Duties of the Role

• Create and maintain optimal data pipeline architecture
• Algorithm Development and Maintenance
• Develop Best Practices and Documentation
• Perform data analysis and data science projects for stakeholders

Basic Qualifications

• Experience with big data tools including Databricks, Snowflake, or similar.
• Service Reliability/Operational experience running large-scale high-performance systems & Internet services
• Ability to write and maintain reliable and understandable code in SQL, Python, Scala, or other languages.

Preferred Qualifications

• 1-2 years of software engineering, machine learning or data science experience
• Familiarity with the end-to-end data lifecycle: from client-side event generation to backend processing and consumption by Data Science models.
• Experience leveraging ML-driven automation to build internal tooling, streamline data pipelines, or enhance observability and monitoring capabilities.
• Familiarity with AI/ML frameworks and platforms and demonstrated ability to evaluate and integrate AI products into existing engineering workflows.

Required Education

Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field of study, or equivalent work experience.