Applied AI Engineer - Fixed Income

Fixed Income Credit Complex team is building an enterprise-grade GenAI workflow platform to power document intelligence, embedded productivity assistants, and automated business workflows across Institutional Securities. This is a production engineering role, not a research or prototype track. We are seeking senior, hands-on engineers who have designed, built, and operated GenAI systems in production environments. This role contributes to a shared platform used across business lines, with a clear path to owning core GenAI capabilities and standards within Institutional Securities.

Role: Applied AI Engineer

Location: New York, NY (1633 Broadway)

Hybrid: 3 days office

Duration: 12+ months

Interview Process:

1.) Zoom

2.) Onsite Interview (90 Mins)

Must:

• Great hands on experience coding within Python
• Good hands on Core AI experience
• Good GenAi and Agentic AI exp
• How it works, how information can be extracted, prompt engineering, etc

Practical experience building applications using Python, OpenAI or Claude Agent SDK and other agentic frameworks (comparable LLM APIs).

•  Strong understanding of prompt engineering, including prompt design, prompt testing, grounding, context management, and output validation.

•   Experience building AI or data-driven applications that use APIs, databases, cloud services, and enterprise data sources.

• Good exp in frontier CodingTools: ClaudeCode - Amp - CodeEx, etc

• Strong RAG Experience - What is needed to implement

• Has working experience working on complex systems and building complex applications
• PostGres Exp
• Although different Vector Database will suffice
• Fantastic Communication skills
• Curious mindset
• Strong Communication (Written and Verbal)
• Know what they are doing, why they are doing it.

Plusses:

• Financial Services Experience (Great if they work with Fixed Income - What is a stock, what is a bond, etc)
• Elastic Search Exp
• Embedding Exp

Misc:

• Doc Central - Massive document repository within the firm
• Becoming the FIRMS main AI solution for document extraction, summarization and search engine for internal documents
• DocCentral is about 20% of the OpenAI traffic through MS
• Doc Central: RAG Millions of Documents
• This person will be using RAG, but also helping build out different capabilities as they scale
• Moved on from Trad RAG, going more Agentic
• Evaluation is also a big component of what they do

Additional Notes:

• AI in interviews is a massive NO
• Needs candidates and their resumes to tell a STORY - not just buzz wordy
• Previous interview Feedback
• Candidates demonstrated fami* with RAG but depth was not there matching the seniority on resume
• Production
• RAG system was relatively smaller in scale/small user base