AI Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, and take ownership of the data pipelines that facilitate the movement and transformation of data from our application and external sources into relational databases, ensuring they remain reliable and well-structured as both volume and complexity increase.

• Collaborate with analytics engineering to develop the data models and reporting mechanisms that provide researchers and teams with clear visibility into their work's performance.

• Prioritize data quality during ingestion, modeling, and reporting. Identify and resolve issues before they impact a model, dashboard, or user experience.

• Develop and deploy production AI systems along with the necessary data infrastructure and services that support machine learning features.

• Create and manage evaluation systems that determine whether an AI feature is ready for deployment and continues to perform well: including evaluation harnesses, test datasets, and production monitoring, all designed as software rather than one-time analyses.

• Establish best practices for data-related work. Communicate clearly, share context proactively, and enhance the efficiency of those around you.

⛳️ Requirements

• Over 5 years of experience in data engineering, with significant exposure to machine learning systems in a production environment.

• Extensive data engineering experience: you have personally designed and managed pipelines that transfer data from application sources into a data warehouse at scale, and you understand the points of failure, when they occur, and the reasons behind them.

• Proficient in Python and well-versed in the data stack, including tools like Snowflake and Postgres.

• Familiarity with orchestration tools such as Airflow, Dagster, or similar technologies.

• Experience in cloud computing environments like GCP or AWS.

• Proven ability to collaborate closely with analytics engineers or data analysts to create reliable and well-documented data models.

• Practical experience in deploying AI or ML systems that real users relied upon in production, along with ownership of the outcomes post-launch.

• A genuine perspective on evaluation: you view evaluations as constructs to be built, rather than mere reports to be generated.

• A high-agency mindset, capable of navigating ambiguous problems and driving them to successful solutions without a fully-defined task.

• Expertise across the data lifecycle, encompassing both production-facing features and the internal analytics that inform decision-making.

• Comfort in utilizing AI coding tools (such as Cursor, Claude Code, Copilot, or similar) as integral components of your workflow.

🏝️ Benefits

• A strong and competitive compensation package that includes a bonus and equity program.

• An exceptional and progressive benefits package (for you and your dependents) that promotes work/life balance, featuring flexible PTO, 15 company holidays, 12 weeks of paid parental leave, a 401k match, and much more.

• An education stipend to support your professional growth and development, along with a remote work stipend.

• A company culture that values openness and transparency, ensuring you are informed about what is happening and why it is important.