AI Engineer

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

📋 Description

• Design, develop, and sustain robust ETL/ELT pipelines integrating on-premise systems, AWS services, and Azure platforms into Snowflake and downstream AI services.

• Create and manage feature stores and analytically optimized datasets to support machine learning workflows.

• Construct generative AI data pipelines, encompassing extraction, transformation, chunking, and loading into vector databases.

• Execute Snowflake data modeling, automate Snowpipe, and optimize compute and storage strategies.

• Carry out non-invasive data extraction from legacy systems while ensuring system stability.

• Design and oversee cross-platform workflows utilizing Airflow, AWS Step Functions, and Azure Data Factory.

• Collaborate with IT, database, infrastructure, and security teams on connectivity, access, and production approvals.

• Establish automated data quality, validation, and observability frameworks.

• Enhance storage, compute usage, and query performance across Snowflake, AWS, and Azure.

• Collaborate with MLOps, Data Science, and AI teams to convert experimental use cases into scalable, production-ready data solutions.

• Perform additional responsibilities as assigned.

⛳️ Requirements

• Preferred: Master’s degree in Computer Science, Data Engineering, or a related field from an accredited institution.

• Required: Six (6) years of practical data engineering experience, with a proven history of constructing production-grade pipelines for Data Science and AI in multi-cloud environments, or an equivalent mix of education and experience.

• Expert-level knowledge in Snowflake architecture, encompassing data sharing, performance tuning, and integration with external cloud AI services.

• Advanced, hands-on expertise with AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services.

• Proficient in Python, SQL, and PySpark.

• Extensive experience with data orchestration and containerization (Docker).

• Demonstrated ability to interact with on-premise SQL, mainframe extracts, and flat files, transforming them for modern cloud utilization.

• Solid understanding of data requirements for Machine Learning, particularly feature engineering.

• Strong comprehension of Generative AI, including vectorization and embedding pipelines.

• Capability to work effectively in a team-oriented environment.

• Ability to meet or exceed Performance Competencies.

• Willingness to travel as required.

🏝️ Benefits

• Work-life balance.

• Reasonable accommodations when applicable and appropriate.

• Equal Opportunity Employer.

• Drug-Free Workplace.