Applied AI Manager

The Role

The Data Science & AI team is growing, and we are looking for an Applied AI Manager to lead our application of AI across the platform and the business. You will work on genuinely hard problems: structured finance data is complex, high-stakes, and largely unstructured, and you will build systems that actually change how the market operates. This is not a research role — we need someone who ships.

What You Will Do

• Lead the design and delivery of complex ML and GenAI systems — robust, scalable, and built for production.
• Guide the team across the full AI lifecycle, from experimentation and evaluation through deployment and monitoring, with a strong focus on reproducibility and reliability.
• Drive architectural decisions for data-intensive, AI-driven applications, making sharp trade-offs between cutting-edge approaches and production readiness.
• Apply NLP and GenAI to extract structure from unstructured financial documents: credit agreements, indentures, and servicer reports.
• Build and deploy models that operate on structured finance data, where a logic error has real financial consequences.
• Mentor and grow engineers across levels, building a high-performing team with a strong engineering culture.
• Collaborate cross-functionally with Product, Data, and Business teams to shape roadmaps and deliver real impact.
• Promote AI adoption across the organization and influence company-wide technology strategy.

What You Bring

• Proven experience leading engineering teams in a fast-paced, high-growth environment.
• Solid understanding of structured finance: loan tapes, cash flow waterfalls, ABS/CLO structures, and priority of payments.
• Strong software engineering skills (Python preferred) combined with deep knowledge of AI/ML frameworks, GenAI tooling, and modern data infrastructure.
• Hands-on experience building and deploying ML/GenAI systems in production within finance, legal, or other high-complexity, data-heavy domains.
• Ability to lead architectural discussions and technical trade-offs without losing sight of the details.
• Familiarity with cloud infrastructure (AWS preferred) and modern MLOps practices.
• Commitment to people development: mentoring, performance conversations, and building high-performing teams.

Bonus

• Experience with NLP on financial contracts, RAG or LLM-based applications on structured data, large-scale loan data pipelines, or containerization tooling (Docker, Kubernetes, Terraform).

Compensation & Benefits

• Competitive salary and performance-based bonus.
• Stock option plan.
• Regular team events and annual retreats.
• Referral bonus program.
• Opportunities for career growth within a fast-scaling fintech innovator.
• A collaborative, innovative, and entrepreneurial culture that values creativity, initiative, and impact.