Lead Data Scientist – AI Engineer
Core
Lead AI Engineer embedded with investment banking deal teams to build AI-powered tools, orchestration layers, and multi-agent applications that automate workflows and deliver measurable business outcomes.
Role type
Senior IC Lead AI Engineer (Investment Banking)
Builds
AI agents, multi-step LLM applications, integration layers between Enterprise Claude/Salesforce/ML models, and data pipelines for feature engineering and model training.
Domain
Investment Banking / Financial Services / Generative AI
Deliverable
production ML models | product features
Required skills
Full-stack software engineering, LLM application development (prompt engineering, RAG, multi-step orchestration), multi-agent ecosystem architecture, ML fundamentals (training, evaluation, feature pipelines), cloud infrastructure (Azure), data platforms (Databricks/Spark), orchestration tools (Dagster/Airflow), Salesforce API integration, security and data governance.
Preferred skills
Forward Deployed Engineer or embedded technical role experience, Salesforce CRM integration patterns, architecting interconnected multi-agent ecosystems, building AI tools for financial professionals, engineering culture mentorship.
Technologies
Azure, Databricks, Spark, Dagster, Airflow, Salesforce, Enterprise Claude, Rogo.ai, Blueflame AI, Fellow.ai
Responsibilities
Design and build integration layers for AI-powered banking workflows; develop AI agents and multi-step LLM applications for high-value use cases; set engineering standards (code review, CI/CD, testing); work directly with deal teams to identify automation opportunities and iterate on tools; build and maintain data pipelines for feature engineering and model training; perform rapid analysis and prototyping; evaluate and integrate point solutions via APIs; implement security and data governance protocols.
Seniority
Senior, hands-on IC with team leadership responsibilities