As part of our team, you will help build an enterprise-grade GenAI workflow platform supporting document data extraction, integrated productivity assistants, and automated business processes across multiple lines of business. This is a production-focused role - not research or prototyping. We are looking for senior, hands-on full-stack engineers who have designed, built, and operated GenAI systems in production, and who understand failure modes, evaluation practices, and governance for mission-critical AI-powered platforms.
Information Security Responsibilities- Promote and enforce awareness of key information security practices, including acceptable use of information assets, malware protection, and password security protocols
- Identify, assess, and report security risks, focusing on how these risks impact the confidentiality, integrity, and availability of information assets
- Understand and evaluate how data is stored, processed, or transmitted, ensuring compliance with data privacy and protection standards (GDPR, CCPA, etc.)
- Ensure data protection measures are integrated throughout the information lifecycle to safeguard sensitive information
Responsibilities:- Design and evolve reusable GenAI workflows used across Lending business lines.
- Develop an enterprise grade AI-based document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review.
- Build AI-powered assistants embedded in Lending systems using agentic workflows.
- Deliver automated content and deck generation workflows for reporting and approvals.
- Provide expert advice on GenAI architecture including model selection, orchestration patterns, and evaluation strategy.
- Establish LLMOps practices: extraction accuracy, assistant reliability, prompts management, and audit monitoring.
- Design and implement controls for entitlements, PII handling within open-source models in a regulated environment.
- In the role you are expected to act as a hands-on technical expert, and it has a clear path to becoming a platform owner responsible for shared GenAI standards across Lending.
Requirements:- 2+, dedicated experience in practical application of GenAI solutions in an enterprise business environment. Designing and operating GenAI orchestration frameworks in production beyond vendor examples (e.g., LangChain systems),
- 5+ years of strong front-to-back engineering experience, focusing on AI ML platforms and workflows (Python or Java).
- Proven experience building and operating production-grade GenAI / LLM platforms, applying patterns such as RAG, tool/function calling, agentic workflows, and validated structured outputs.
- Strong LLMOps expertise, including evaluation harnesses, prompt and version management, regression testing, observability, and reliability measurement in production systems.
- Hands-on experience building AI-first data ingestion pipelines with measurable quality, accuracy, and reliability.
- Advanced retrieval experience advanced vector search, including multi-vector and late-interaction approaches (e.g., ColBERT, chunking), multi-stage retrieval pipelines, metadata filtering, re-ranking. Solid understanding of evaluation metrics and how they shape practical RAG system design (e.g., recall vs precision, latency vs quality, MRR, NDCG).
- Experience operating GenAI systems through real production failures (model regressions, retrieval degradation, prompt drift, data quality issues) and designing mitigation strategies.
Nice to Have:- Fixed Income or Institutional Lending domain experience.
- Experience working in regulated environments with strong audit and control requirements.
- Familiarity with enterprise security, data governance, and entitlement models.
- Experience designing reusable internal platforms or shared developer tooling.
- Frontend experience is beneficial (Angular or React)
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