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Generative AI Engineer at Qode. About the Role. Join our innovative team as a Generative AI Engineer, where you’ll design and maintain cutting-edge data pipelines to fuel actionable insights. You’ll collaborate with data analysts and business stakeholders to enhance operational efficiency and elevate customer satisfaction through advanced data engineering and AI-driven solutions. This remote role offers the opportunity to make a meaningful impact in a dynamic, fast-paced environment.. Job Title: Generative AI Engineer. Location: Remote (US-based, excluding CA and HI) – must work EST hours. Employment Type: Contract-to-Hire. Pay Rate: $45–47/hour (target). Key Responsibilities. . . Data Pipeline Development. : Build and maintain robust ETL (Extract, Transform, Load) pipelines to process data from diverse sources, including CRM and call center systems, ensuring seamless integration into data warehouses and lakes.. . . Data Modeling. : Create dimensional and analytical data models to support business reporting and analytics needs, accurately reflecting business domains.. . . Data Integration. : Automate data ingestion and transformation processes, resolving inconsistencies to ensure data integrity across multiple sources.. . . Data Quality Assurance. : Implement checks to monitor and maintain data accuracy and completeness, proactively addressing quality issues.. . . Performance Optimization. : Enhance data pipelines and queries for efficient processing, ensuring timely delivery of insights.. . . Collaboration. : Partner with data analysts, business stakeholders, and data science teams to translate business needs into technical solutions, supporting advanced analytics and machine learning initiatives.. . Qualifications. . . Experience. : 3–5 years in data engineering, with strong expertise in ETL processes, data warehousing, and contact center AI/ML applications.. . . Technical Skills. :. . Proficiency in SQL, Python (for ETL, data integration, and modeling), and Java.. . Expertise with data integration tools (e.g., Informatica, Talend, or Apache Airflow).. . Strong knowledge of relational and NoSQL databases, cloud platforms (AWS or Google Cloud), and big data technologies (Hadoop, Spark).. . Experience with data manipulation tools (e.g., Pandas) and version control systems.. . Familiarity with AI/ML fundamentals, model deployment, and data preparation.. . . Industry Knowledge. : Understanding of data privacy, regulatory compliance, and customer feedback measurement in AI projects.. . . Education. : Bachelor’s degree in Computer Science, Engineering, or a related field.. . Company Location: United States.