Lead Data Scientist - AI Engineer

Responsibilities

• Design and build the integration layer between Enterprise Claude, Salesforce CRM, and proprietary ML models for AI-powered banking workflows.
• Develop AI agents and multi-step LLM applications for document generation, buyer analysis, process-letter drafting, and deal-status automation.
• Set engineering standards covering architecture, code reviews, CI/CD pipelines, testing frameworks, deployment patterns, and documentation.
• Work directly with deal teams and industry groups to identify automation opportunities and iterate on deployed tools using banker feedback.
• Build and maintain Databricks and Dagster data pipelines for feature engineering, model training, and analytics.
• Rapidly prototype solutions that translate banker pain points into working proofs of concept.
• Evaluate and integrate Rogo.ai, Blueflame AI, and Fellow.ai through APIs within Salesforce.
• Implement security and data-governance protocols for confidential deal information.
• Operate production multi-agent ecosystems with monitoring, failure recovery, reliability practices, and scaling.

Requirements

• 5+ years of software engineering experience with a strong full-stack foundation and production experience serving demanding end users.
• Hands-on experience building applications or agents with large language models, including prompt engineering, retrieval-augmented generation, multi-step orchestration, tool use, and evaluation frameworks.
• Experience deploying and operating production multi-agent ecosystems, including reliability engineering, monitoring, failure recovery, and scaling.
• Strong machine-learning fundamentals, including model training, evaluation, deployment, exploratory data analysis, and feature-pipeline development.
• Experience writing tested, reviewed, documented, and maintainable production code.
• Familiarity with capital markets and preferably investment banking, private equity, venture capital, or hedge funds.
• Experience with cloud infrastructure, preferably Azure, and data platforms and orchestration tools such as Databricks, Spark, Dagster, or Airflow.
• Preferred experience in forward deployed, solutions engineering, or embedded technical roles with ownership of business outcomes.
• Preferred experience with Salesforce APIs, SOQL, CRM integration patterns, and production-grade interconnected multi-agent ecosystems.
• Preferred experience building AI tools for financial professionals and contributing to engineering culture through mentoring or technical design leadership.

Benefits

• Hybrid work arrangement, indicated by the #LI-HYBRID designation.
• Base salary range of $186,000–$222,000, plus eligibility for a discretionary annual bonus and/or commission-based incentives.
• Medical, dental, and vision coverage; employer-paid short- and long-term disability and life insurance; 401(k); profit sharing; and paid time off.
• Maven family and fertility benefits and parental leave, including adoption, surrogacy, and foster placement.
• Additional voluntary benefits.