Senior Staff Data Engineer - AI Solutions

Circle is a financial technology company at the epicenter of the emerging internet of money, where value can finally travel like other digital data — globally, nearly instantly and less expensively than legacy settlement systems. This ground-breaking new internet layer opens up previously unimaginable possibilities for payments, commerce and markets that can help raise global economic prosperity and enhance inclusion. Our infrastructure – including USDC, a blockchain-based dollar – helps businesses, institutions and developers harness these breakthroughs and capitalize on this major turning point in the evolution of money and technology.

What you’ll be part of:

Circle is committed to visibility and stability in everything we do. As we grow as an organization, we're expanding into some of the world's strongest jurisdictions. Speed and efficiency are motivators for our success and our employees live by our company values: Multistakeholder, Mindfulness, Driven by Excellence and High Integrity. Circlers are consistently evolving in a remote world where strength in numbers fuels team success. We have built a flexible and diverse work environment where new ideas are encouraged and everyone is a stakeholder.

What You’ll Be Responsible For:

As a Senior Staff Data Engineer specializing in AI solutions, you will drive the design and development of innovative data architectures and pipelines that support the training of AI models and enhance the integration of data into AI platforms. Your expertise will play a crucial role in advancing our AI initiatives and enabling smarter decision-making across the organization. You will collaborate with cross-functional teams to ensure that high-quality, scalable, and efficient data solutions are implemented, laying the foundation for AI-powered insights and products.

What You'll Work On:

• Design and implement robust data architectures and ETL/ELT pipelines specifically tailored for AI model training and data ingestion into AI platforms.

• Develop and maintain feature stores to serve as centralized repositories for dynamic, high-quality features crucial for training and serving AI models. Ensure easy access to and versioning of features for data scientists and AI engineers.

• Collaborate with data scientists and AI engineers to understand data requirements, optimize data flows, and enable seamless access to high-quality data for model training.

• Build automation and monitoring capabilities around feature engineering processes, including real-time feature computation and batch processing, to enhance model training efficiency.

• Implement data governance and quality assurance practices to ensure the integrity, accuracy, and reliability of the data and features used in AI applications.

• Explore and integrate new data technologies and tools that enhance data processing efficiencies and support AI initiatives.

• Mentor and lead junior data engineering staff, promoting guidelines and innovative solutions within the data engineering community.

• Collaborate with stakeholders across product, engineering, and analytics teams to identify and prioritize opportunities to drive AI initiatives and improve business outcomes.

You Will Aspire to Our Core Values:

• Multistakeholder: You are dedicated to fostering relationships with customers, shareholders, employees, and the community, effectively balancing their needs and priorities.

• Mindful: You demonstrate a keen attention to detail and the ability to actively listen, ensuring a respectful and inclusive work environment.

• Driven by Excellence: Your commitment to excellence drives every aspect of your work, pursuing high-impact outcomes while refusing to accept mediocrity.

• High Integrity: You uphold the highest moral and ethical standards, promoting transparent communication and trust among your teams and stakeholders.

What You’ll Bring to the Team:

• 10+ years of experience in data engineering, with a focus on building data solutions for AI and machine learning applications.

• Advanced proficiency in SQL and expertise in data warehouse technologies such as BigQuery, Snowflake, or Databricks, enabling effective data management and optimization.

• Strong coding skills in programming languages such as Python or Scala, with experience in frameworks commonly used for machine learning and AI (e.g., TensorFlow, PyTorch).