We are representing a high-performing boutique private credit investment firm building proprietary AI capability internally.They are not hiring a data support analyst.They are hiring the engineer who will help build the AI backbone of an investment platform.This role is for the top 5% of early-career engineers who want ownership, commercial exposure, and the chance to build systems that directly influence capital allocation decisions.The MandateDesign and build the data infrastructure that will power:AI-assisted underwritingPortfolio risk surveillanceAutomated covenant monitoringLLM-driven document intelligenceProprietary credit analyticsYou will work directly with investors deploying capital — not in a siloed tech team.Your work will influence live investment decisions.What Makes This DifferentNo legacy bureaucracyNo passive dashboard maintenanceDirect access to decision-makersHigh accountabilityVisible impactThis is a build environment.The firm is early in its AI journey. The right candidate will shape architecture, tooling, and standards.What You’ll Actually DoBuild scalable ETL/ELT pipelines from loan systems and financial dataStructure complex borrower reporting (financial statements, PDFs, credit memos)Design clean datasets for predictive credit risk modelsEnable LLM/RAG pipelines for document intelligenceImplement data quality, validation, and monitoring frameworksPartner with credit investors to translate underwriting logic into data systemsThis is production engineering in a high-stakes financial environment.Who We’re Looking ForYou are likely:1–3 years into your engineering careerStrong in Python and SQLComfortable working in cloud environments (AWS/GCP/Azure)Experienced building real pipelines — not just notebooksCurious about how financial systems actually workBonus points for:Exposure to ML workflowsFamiliarity with dbt, Airflow, DockerExperience handling financial or semi-structured dataInterest in LLM infrastructure and vector databasesFinance background is not required.Intellectual horsepower and ownership mentality are.This Role Is Not For You IfYou prefer clearly defined, low-risk task listsYou want heavy supervisionYou are uncomfortable working directly with senior stakeholdersYou are looking for a purely academic ML roleUpsideDirect learning from investorsRapid technical growthPath toward AI Engineer / ML Engineer / Quant Data rolesHigh visibility within a compact, performance-driven firmCompensation aligned to performanceThis is an opportunity to build proprietary AI systems inside a capital allocation business — early.For the right engineer, this is career-accelerating.