Applied AI Manager
Role details
Job location
Tech stack
Job description
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 DoLead 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
Requirements
and Business teams to shape roadmaps and deliver real impact.Champion AI adoption across the organization and influence company-wide technology strategy.What You BringProven 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).Competitive salary and performance-based bonus.Stock option plan.Regular team events and annual retreats.Opportunities for career growth within a fast-scaling fintech innovator.A collaborative, innovative, and entrepreneurial culture that values creativity, initiative, and impact. #J-18808-Ljbffr