Applied AI Engineer

Machine Learning Expert

Exp: 14+ Years

Must Have:

• Strong background within machine learning
• Everything within AI starts here
• Strong within Python (not looking for a software developer who has learned how to use models. Instead, looking for a core math background, machine learning, data model extraction and/or trading models)
• Pytorch
• Langchain
• Core AI tools
• Document extraction experience and comfortable enhancing the model to produce better extraction
• RAG experience is a must
• Agentic workflows experience
• Ability to orchestrate workflows of a system. Someone who has applied their knowledge into applying agentic workflows - move through steps from beginning to end. Do transformation on it and produce a result
• LLM OPS
• Not looking for a software dev who learned how to use models
• Building production systems and not just trying to learn something
• Someone who has applied knowledge into how effectively they can apply agentic workflows
• Must have professional experience working with a live system, opposed to someone doing this recreationally
• Financial services is a huge plus

Plus:

• Engineering experience front to back
• Build workflows, examine systems, suggest solutions to it using data flows and gen AI, etc
• 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)

D2D;

• 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

Misc:

• They do not have this type of candidate on team today - they need this candidate to come in and be a SME on the team and be confident enough to bring their own two sense into the role
• AI platform is being built from scratch
• Need this candidate to bring knowledge of how to chain workflows and how to enhance extractions
• Stakeholders
• Strats (heavy math background) + Operations users + Business users
• Current volume of documents: Lending volume is massive
• Docs can go from 1 page to 300+ pages (PDFs)

Redflags:

• Developer who simply is using AI

Ideal Candidate:

• Applied AI SME - how can come in and say "This is how it needs to be done, this is what I will need to do it, this is my timeline, etc."
• Practitioner is someone who not just someone giving out straight answer