Applied AI Engineer

Applied AI Engineer



Location: New York, NY (Hybrid 4 5 days onsite)



Duration: 12 months



Interview Process: 1st Round Zoom | 2nd Round In-Person

Note:

• Must be local with DL copy
• LinkedIn with location (before 2022)
• Recent or recent second project must be at the current location

Ideal Candidate

The ideal candidate is an Applied AI SME and practitioner who can walk into a greenfield environment and confidently say:

"This is how the solution should be built, these are the capabilities we need, these are the challenges we need to address, and this is how I would deliver it."

They should be comfortable working directly with technical and business stakeholders and be capable of architecting, building, evaluating, and improving AI systems themselves .

Key distinction: We are looking for someone who has applied AI-not simply someone who uses AI. Candidates whose experience is primarily traditional software development with AI APIs/LLMs layered on top will not be a strong fit.

Job Description

Client is seeking a highly experienced Applied AI Engineer / AI SME to help build a new enterprise-grade AI platform supporting the Lending business.

This is a hands-on Applied AI role for a practitioner with a strong foundation in Machine Learning, Python, document intelligence, RAG, Agentic AI, and LLMOps. The ideal candidate is not a software developer who has simply learned how to use AI models . We are looking for someone with strong core ML and mathematical knowledge who has applied AI to real-world, production systems.

The AI platform is being built from scratch, so this person will be expected to act as a technical SME , bring their own expertise and recommendations, and help define how AI workflows, document extraction, model enhancement, and agentic systems should be designed and implemented.

Required Skills

• Strong background in Machine Learning / Artificial Intelligence with solid mathematical and analytical fundamentals.
• Strong hands-on Python experience.
• Experience with PyTorch and modern AI/GenAI frameworks such as LangChain .
• Strong experience with document extraction/document intelligence and improving extraction quality.
• Production RAG experience is mandatory.
• Strong hands-on experience building Agentic AI workflows and orchestrating multi-step AI systems.
• Experience with LLMOps and operating LLM/GenAI systems in production.
• Demonstrated experience building and supporting live production AI systems , not just prototypes or personal projects.
• Ability to take an ambiguous AI problem and independently determine the architecture, approach, required resources, and delivery plan.
• Strong understanding of AI model evaluation, reliability, scalability, and monitoring.

Qualifications

• Financial Services experience is a major plus .
• Experience with Fixed Income, Institutional Lending, Capital Markets, or related domains .
• Experience working in regulated environments with strong audit, controls, security, and governance requirements.
• Familiarity with enterprise data governance and entitlement models.
• Experience designing reusable internal AI platforms or shared developer tooling.
• Full-stack engineering experience is beneficial.
• Frontend experience with React or Angular is a plus.