AI (PRODUCT) Engineer

Role Summary

This position involves developing and maintaining production-level decisioning and data processing systems within a highly rules-driven enterprise environment.

The role requires hands-on engineering expertise in Python, data pipelines, and enterprise AI deployment, with a focus on scalable, reliable, and maintainable solutions.

It is ideal for professionals experienced in integrating AI technologies and building complex workflows in cloud-based platforms.

Responsibilities

• Translate complex business rules and domain logic into clean, testable decisioning systems.
• Design, develop, and support scalable Python-based data processing and decision pipelines utilizing Databricks, PySpark, and Pandas.
• Build and maintain enterprise data workflows within the Databricks platform, ensuring efficiency and reliability.
• Integrate internal and external APIs with robust error handling, retries, and fault tolerance.
• Develop modular components suitable for orchestrated, production-grade workflows.
• Incorporate enterprise AI and Large Language Model services, including Azure AI Foundry and OpenAI, as needed, with appropriate prompt and template configurations.
• Apply data security and compliance standards, including PII handling, input/output validation, and structured logging.
• Implement monitoring, logging, and troubleshooting strategies to support production environments.
• Participate in version control activities including branching, code reviews, and conflict resolution using Git.
• Support and troubleshoot live production systems to ensure operational stability.

Qualifications

• Extensive hands-on experience with Python engineering for enterprise data and decision systems.
• Proven expertise with Databricks for data engineering and production pipeline development.
• Experience with Azure AI Foundry and deploying enterprise AI solutions.
• Advanced skills in PySpark and Pandas.
• Demonstrated experience in implementing rule-based decision logic and decision systems.
• Familiarity with integrating OpenAI, LLMs, and AI-assisted workflows in enterprise applications.
• Solid understanding of Git-based development workflows.
• Practical experience with Azure DevOps, CI/CD pipelines, and deployment monitoring.
• Proven ability to support and troubleshoot enterprise production environments.

Publishing Pay Range

$74.31 - $77.68 Hourly

This is a fully remote role and can be performed from an approved location.