Lead Engineer (AI/ML - Rule Ops) na Prodapt

Join the Prodapt team in building a unified, cloud-native environment for authoring, simulating, deploying, and monitoring business and risk rules at scale. You will help design, develop, and optimize robust RuleOps workflows that empower risk analysts, data scientists, and engineers to efficiently manage and operationalize rules with strong support for simulation, governance, and integration.

• Develop, maintain, and enhance custom rule authoring interfaces and engines for business and risk logic.
• Build and optimize data processing and feature computation workflows using PySpark, Databricks, and event-driven architectures (Kafka).
• Integrate with DB for rule storage, state management, and result persistence; leverage blob storage and Delta tables for raw and processed data.
• Containerize and orchestrate rule evaluation services using Docker and Kubernetes (GKE) for scalable deployment.
• Implement and support simulation and backtesting platforms for historical data replay, feature simulation, and rule validation.
• Develop RESTful APIs and SDKs for rule management, evaluation, and integration with upstream/downstream systems.
• Ensure robust monitoring, governance, and security, including real-time dashboards, role-based access control (RBAC), and audit logging.
• Collaborate with risk analysts, data scientists, ML engineers, and platform teams to deliver reliable, production-grade RuleOps solutions.
• Participate in code reviews, architecture discussions, and continuous improvement of the RuleOps platform.

Required Technical Skills

• Proficiency in Python for backend development and data engineering.
• Experience with PySpark, Databricks, and event-driven data processing (Kafka).
• Hands-on experience with blob storage, and Delta tables.
• Experience with Docker for containerization and Kubernetes (GKE) for orchestration.
• Familiarity with RESTful API development and SDK integration.
• Strong understanding of simulation, backtesting, and validation workflows for rules.
• Knowledge of security best practices, RBAC, and compliance requirements.
• Excellent troubleshooting, debugging, and communication skills.

Preferred Qualifications

• Experience with simulation platforms (e.g., AI Sigma Simulation) and synthetic event generation.
• Familiarity with large-scale financial/risk platforms.
• Exposure to dashboarding, monitoring, and operational health tools for rule evaluation.
• Experience with workflow automation and integration with Atlassian tools (Jira, Confluence).
• Knowledge of data privacy, vulnerability scanning, and compliance automation.

What We Offer

• Opportunity to work on a high-impact, enterprise-scale RuleOps platform.
• Collaborative, innovative, and inclusive team culture.
• Access to the latest tools and technologies in rule management, data engineering, and cloud-native development.
• Career growth and learning opportunities.