{
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  "job_title": "AI Data Engineer for Private Credit",
  "job_country": "GB",
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  "job_location": "United Kingdom",
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      "publisher": "Talents By StudySmarter",
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  "employer_name": "Winston Fox",
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  "job_posted_at": "25 days ago",
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  "job_description": "We are representing a high-performing boutique private credit investment firm building proprietary AI capability internally.\n\nThey are not hiring a data support analyst.\n\nThey are hiring the engineer who will help build the AI backbone of an investment platform.\n\nThis 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.\n\nThe Mandate\n\nDesign and build the data infrastructure that will power:\n• AI-assisted underwriting\n• Portfolio risk surveillance\n• Automated covenant monitoring\n• LLM-driven document intelligence\n• Proprietary credit analytics\n\nYou will work directly with investors deploying capital — not in a siloed tech team.\n\nYour work will influence live investment decisions.\n\nWhat Makes This Different\n• No legacy bureaucracy\n• No passive dashboard maintenance\n• Direct access to decision-makers\n• High accountability\n• Visible impact\n\nThis is a build environment.\n\nThe firm is early in its AI journey. The right candidate will shape architecture, tooling, and standards.\n\nWhat You’ll Actually Do\n• Build scalable ETL/ELT pipelines from loan systems and financial data\n• Structure complex borrower reporting (financial statements, PDFs, credit memos)\n• Design clean datasets for predictive credit risk models\n• Enable LLM/RAG pipelines for document intelligence\n• Implement data quality, validation, and monitoring frameworks\n• Partner with credit investors to translate underwriting logic into data systems\n\nThis is production engineering in a high-stakes financial environment.\n\nWho We’re Looking For\n\nYou are likely:\n• 1–3 years into your engineering career\n• Strong in Python and SQL\n• Comfortable working in cloud environments (AWS/GCP/Azure)\n• Experienced building real pipelines — not just notebooks\n• Curious about how financial systems actually work\n\nBonus points for:\n• Exposure to ML workflows\n• Familiarity with dbt, Airflow, Docker\n• Experience handling financial or semi-structured data\n• Interest in LLM infrastructure and vector databases\n\nFinance background is not required.\n\nIntellectual horsepower and ownership mentality are.\n\nThis Role Is Not For You If\n• You prefer clearly defined, low-risk task lists\n• You want heavy supervision\n• You are uncomfortable working directly with senior stakeholders\n• You are looking for a purely academic ML role\n\nUpside\n• Direct learning from investors\n• Rapid technical growth\n• Path toward AI Engineer / ML Engineer / Quant Data roles\n• High visibility within a compact, performance-driven firm\n• Compensation aligned to performance\n\nThis is an opportunity to build proprietary AI systems inside a capital allocation business — early.\n\nFor the right engineer, this is career-accelerating.",
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  "employer_website": "https://www.winston-fox.co.uk",
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  "job_salary_period": "YEAR",
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  "job_employment_type": "Full–time",
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  "job_posted_at_timestamp": 1771891200,
  "job_posted_at_datetime_utc": "2026-02-24T00:00:00.000Z"
}