Description

You will work toward becoming a platform owner responsible for shared GenAI standards across the Lending business.

Responsibilities

• Design and evolve reusable GenAI workflows used across Lending business lines.
• Build an enterprise-grade AI document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review.
• Develop AI-powered assistants embedded in Lending systems using agentic workflows.
• Deliver automated content and deck generation workflows for reporting and approvals.
• Advise on GenAI architecture: model selection, orchestration patterns, and evaluation strategy.
• Establish LLMOps practices covering extraction accuracy, assistant reliability, prompt management, and audit monitoring.
• Design and implement controls for entitlements and PII handling, including safe use of open-source models in a regulated environment.

Qualifications

• Required
  • 5+ years of front-to-back engineering experience in Python or Java, with a focus on AI/ML platforms and workflows.
  • 2+ years of dedicated, practical GenAI experience in an enterprise business environment, including designing and operating orchestration frameworks in production beyond vendor examples (e.g., custom LangChain-based systems).
  • Proven experience building and operating production-grade GenAI/LLM platforms applying RAG, tool/function calling, agentic workflows, and validated structured outputs.
  • Strong LLMOps expertise: evaluation harnesses, prompt and version management, regression testing, observability, and reliability measurement in production.
  • Hands-on experience building AI-first data ingestion pipelines with measurable quality, accuracy, and reliability.
  • Advanced retrieval depth: multi-vector and late-interaction approaches (e.g., ColBERT), chunking strategy, multi-stage retrieval pipelines, metadata filtering, and re-ranking—plus working command of evaluation metrics (recall vs. precision, latency vs. quality, MRR, NDCG) and how they shape RAG design.
  • Experience operating GenAI systems through real production failures—model regressions, retrieval degradation, prompt drift, data quality issues—and designing mitigations.
• Preferred
  • Fixed Income or Institutional Lending domain experience.
  • Experience in regulated environments with strong audit and control requirements.
  • Familiarity with enterprise security, data governance, and entitlement models.
  • Experience building reusable internal platforms or shared developer tooling.
  • Frontend experience (Angular or React)

Key Skills

Education

Any Graduate