Lead Engineer, Pricing & Decision Systems

About the role

Core responsibilities

• Own the AWS-based Python pricing and decision engine, including its pricing logic and production reliability.
• Integrate scoring models and maintain offer grids, modifiers, rates, fees, and offer-sizing rules.
• Lead and mentor engineers, set architecture and review standards, and oversee risky pricing changes.
• Maintain correct DynamoDB and S3 data, audit records, experiment history, and versioned reference files.
• Build reconciliation, quality, monitoring, and health-dashboard capabilities.
• Design and analyze A/B tests and maintain experiment-data integrity.
• Own sales-platform, CRM, credit-provider, and bank-data integrations.
• Partner with Product, DevOps, Data Engineering, Data Science, and QA on delivery and operations.
• Use modern AI and LLM tooling for prototyping, documentation, testing, and delivery.

Role growth

• Integrate machine-learning models into production pricing and decision flows with Data Science.
• Build internal analytics applications and data products such as automated reporting and decision-support tools.
• Own the storage, data plumbing, and quality checks supporting analytics applications and models.
• Set engineering standards and technical direction for analytics development as the team grows.

Requirements

• 5+ years of professional Python development with production applications and services.
• Experience leading or mentoring engineers and directing a small team's work.
• Experience building REST APIs and operating production AWS services, including ECS/Fargate, DynamoDB, S3, Lambda, SQS, Secrets Manager, and CloudWatch.
• Strong SQL and experience with relational and NoSQL data, CSV, Parquet, data modeling, and validation.
• Experience integrating machine-learning or analytical model outputs into production systems.
• Experience with A/B testing, experimentation, data correctness, and reconciliation or quality checks.
• Strong cross-team communication, self-directed ownership, and comfort using AI and LLM tools.

Nice to have

• Background in financial services, lending, or pricing systems.
• Experience with Salesforce, HubSpot, CI/CD, Docker, dbt, Airflow, Next.js, or TypeScript.
• Experience with AI infrastructure, agents, model serving, monitoring, retraining pipelines, MLflow, or SageMaker is advantageous.

Benefits

• Benefits include health, dental, vision, medical bridge, 401k matching, identity protection, life insurance, paid time off, and holidays.

About One Park Financial