Generative AI Engineer

What you’ll do

• Apply the knowledge of data characteristics and data supply pattern, develop rules and tracking process to support data quality model. 

• Prepare data for analytical use by building data pipelines to gather data from multiple sources and systems.

• Integrate, consolidate, cleanse and structure data for use by our clients in our solutions.

• Perform design, creation, and interpretation of large and highly complex datasets.

• Stay up-to-date with the latest trends and advancements in GCP and related technologies, actively proposing and evaluating new solutions.

• Understand best practices for data management, maintenance, reporting and security and use that knowledge to implement improvements in our solutions.

• Implement security best practices in pipelines and infrastructure.

• Develop and implement data quality checks and troubleshoot data anomalies.

• Provide guidance and mentorship to junior data engineers.

• Review dataset implementations performed by junior data engineers.

What experience you need

• BS degree in a STEM major or equivalent discipline; Master’s Degree strongly preferred

• 5+ years of experience as a data engineer or related role

• Cloud certification strongly preferred

• Advanced skills using programming languages such as Python or SQL and intermediate level experience with scripting languages

• Intermediate level understanding and experience with Google Cloud Platforms and overall cloud computing concepts, as well as basic knowledge of other cloud environments

• Experience building and maintaining moderately-complex data pipelines, troubleshooting issues, transforming and entering data into a data pipeline in order for the content to be digested and usable for future projects 

• Experience designing and implementing moderately complex data models and experience enabling optimization to improve performance

• Demonstrates advanced Git usage and CI/CD integration skills

What could set you apart

• Master’s degree in a related field is a strong plus

• Exposure in Vertex AI, GCP AI/ML services (AutoML, BigQuery ML, Cloud Run, etc.) or a similar cloud technology

• Strong foundational skills in Linux Operating System.

• Understanding of NLP, deep learning, and generative architectures (Transformers, Diffusion Models, etc.)

• Background in credit risk, financial data analytics or risk modeling.

• Experience working with large datasets on a big data platform (e.g., Google Cloud, AWS, Snowflake, Hadoop)

• Experience in Business Intelligence, data visualization, and customer insights

• generation.

• Familiarity with data governance, model bias mitigation, and regulatory frameworks (GDPR, AI Act, SEC compliance).

• Experience with MLOps practices, model monitoring, and CI/CD for AI workflows.

• Knowledge of prompt tuning, fine-tuning, and parameter-efficient methods (LoRA, PEFT).

• Hands-on experience with RAG, multi-modal AI, and hybrid AI architectures.

• Contributions to the AI community through publications, open-source projects, or conference presentations.