AI Data Engineer (US)

AI Data Engineer

Experience: 2–7 Years

Location: San Francisco, CA | New York, NY | Seattle, WA | Dallas, TX

Salary: $115,000–$195,000+ per year

Job Type: Full-Time

About the Role

We are looking for an experienced AI Data Engineer to build scalable data pipelines, cloud-based data platforms, and high-quality datasets that power modern AI and machine learning applications. The ideal candidate has strong expertise in Python and SQL, solid data engineering fundamentals, and hands-on experience with cloud technologies and ML workflows.

Key Responsibilities

- Design, develop, and maintain scalable ETL/ELT and data pipelines.

- Build and optimize data infrastructure supporting AI/ML applications.

- Develop reliable data processing solutions using Python and SQL.

- Integrate data from databases, APIs, applications, and other sources.

- Design data models, data warehouses, and analytics-ready datasets.

- Prepare, transform, validate, and optimize datasets for machine learning.

- Collaborate with Data Scientists, ML Engineers, Software Engineers, and business teams.

- Implement data quality, monitoring, governance, and security best practices.

- Optimize data pipelines and cloud infrastructure for performance, scalability, and reliability.

- Support ML model training, deployment, and production data workflows.

- Troubleshoot data and pipeline issues and continuously improve system performance.

Required Qualifications

- 2–7 years of experience in Data Engineering, AI/ML Engineering, or a related field.

- Strong hands-on experience with Python and SQL.

- Solid understanding of data engineering, data modeling, ETL/ELT, and data warehousing.

- Working knowledge of machine learning concepts and AI data workflows.

- Experience with at least one major cloud platform: AWS, Azure, or Google Cloud.

- Experience working with relational and analytical databases.

- Strong understanding of data integration, APIs, and distributed data processing.

- Ability to work effectively in a collaborative, fast-paced environment.

Preferred Qualifications

- Experience with Apache Spark, Databricks, Airflow, Kafka, or similar technologies.

- Experience with Snowflake, BigQuery, Redshift, or other modern data warehouses.

- Knowledge of GenAI, LLM, RAG, vector databases, or AI application pipelines.

- Experience with Docker, Kubernetes, CI/CD, and cloud infrastructure.

- Familiarity with MLOps and production machine learning systems.

- Experience building highly scalable and reliable cloud data platforms.

What We Offer

- Competitive salary: $115K–$195K+

- Health, dental, and vision benefits

- 401(k) and retirement benefits

- Paid time off and holidays

- Professional development opportunities

- Flexible/hybrid work options, depending on role and location

- Opportunity to work with modern AI, ML, data, and cloud technologies