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Applied AI Engineer

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Onsite

Applied AI Engineer

Pagaya Investments

Applied AI Engineer

Skills

SQL QueriesLookerBig DataData EngineeringTableauTypescriptPythonData ScienceData AnalysisAINo-code AutomationsBusiness TransformationPower BIJavascript

2 months ago

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Important information


Salary:

$140,000 – $170,000 / year

Location:

New York, NY, USA

Work mode:

Onsite

Published on:

18 August 2026

What they need


Who you are

  • Experience: 4+ years of experience in data engineering, business intelligence, or software engineering with demonstrated hands-on experience building applied AI solutions, internal tools, or AI-driven automations
  • Business Intelligence Core: Strong mastery of SQL, data modeling, BI tools (e.g., Tableau, PowerBI, Looker), and experience processing, analyzing, and structuring large data sets
  • Technical & Coding Proficiency: Advanced proficiency in Python (or JavaScript/TypeScript) for data manipulation, backend scripting, and rapid software prototyping; comfort generating, debugging, and refactoring AI-generated code
  • Modern AI Tooling & Frameworks: Hands-on experience with modern LLM APIs/ecosystems (OpenAI, Claude, Gemini), agentic orchestration frameworks, RAG (Retrieval-Augmented Generation) architectures, and enterprise AI platforms
  • Communication & Stakeholder Management: Exceptional written and verbal communication skills with a proven track record of distilling technical and financial concepts for non-technical leadership and cross-functional teams
  • Adaptability & Drive: An entrepreneurial mindset with the ability to manage multiple complex, fast-paced projects simultaneously, delivering meticulously accurate, self-audited work within tight deadlines
  • Education: Bachelor’s degree in Computer Science, Data Science, Information Systems, Finance, Engineering, or an equivalent quantitative discipline required
  • Preferred: Prior exposure to financial services, structured finance, fixed income, or capital markets workflows is a strong plus

What the job involves

  • As an Applied AI Engineer embedded within the Office of the CEO and President (OCEO/OOP), you will serve as a high-impact builder driving the future of AI-enabled business transformation at Pagaya
  • Working at the intersection of business strategy, data architecture, and modern artificial intelligence, you will build and deploy practical, high-value AI solutions, automations, and intelligent agents that modernize internal workflows
  • Starting within the OCEO/OOP to address high-visibility executive priorities, your work will quickly expand to partner with key business functions across Capital Markets, Finance, and broader Operations
  • Combining a strong background in Business Intelligence (BI) with hands-on AI engineering capabilities, you will translate complex financial workflows into durable, scalable AI systems that elevate operational speed and analytical precision across the company
  • Embedded AI Development: Act as the primary technical builder, advisor, and problem-solver for AI-enabled workflow transformations - starting in the OCEO/OOP and expanding into Capital Markets, Finance, and key operational units
  • Workflow Automation & Agentic Systems: Identify manual, repeated, or data-dense business processes and build production-ready AI tools, customized copilots, and agentic workflows to streamline execution
  • BI & Data Integration: Leverage a robust background in Business Intelligence and data analysis to connect LLMs, foundation models, and AI agent frameworks directly into Pagaya’s data infrastructure, dashboards, and financial models
  • Cross-Functional Execution: Work closely with business leadership, financial analysts, and capital markets teams to translate ambiguous business problems and complex financial data into practical, user-friendly technical solutions
  • Rapid Prototyping & Scale: Design, iterate, and deploy prototypes rapidly based on stakeholder feedback, while adhering to enterprise standards for data security, governance, and responsible AI usage
  • Enablement & Documentation: Templatize and document solutions to enable scalable reuse across departments; lead walkthroughs and light enablement to drive active user adoption across technical and non-technical teams

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