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Strong employer brand, metro location, mid-level AI role and broad required skills drive high applicant density.
Requires enterprise AI/LLM and domain-specific (Finance/HR) experience, so fit is moderately industry-sensitive.
Explicit 5+ years plus mandatory LLM, MLOps, cloud, and enterprise platform skills increase screening rigidity.
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Design and implement scalable AI analytics pipelines and agentic workflows for Enabling Functions like Finance, HR, Procurement, and Legal.
Integrate and operationalize large language models (LLMs), predictive models, and multi-agent frameworks ensuring enterprise-grade model reliability, reproducibility, and performance using AWS, Palantir Foundry, Snowflake.
Collaborate with Product Owners, Data Engineers, and Data Scientists in agile teams to deliver AI solutions embedding explainability, transparency, and security, and support AI consumption via APIs, dashboards, and embedded analytics.
University degree or equivalent in Mathematics, Physics, Computer Science, or related field.
5+ years experience in data science, data engineering, analytics, or application design in global organizations with exposure to Finance, HR, or Procurement data/processes.
Proficient in Python, SQL, machine learning, statistics, predictive modeling, NLP, and practical experience with LLM-powered applications.
Experience with cloud/data platforms (AWS, Palantir Foundry, Snowflake), data transformation frameworks (Apache Spark, Polars, DuckDB, dbt), and MLOps/DevOps tools (MLflow, CI/CD, Docker).
Experienced with vector stores, reranking, LLM observability tools (Langfuse, LangSmith) and agentic engineering tools within enterprise software development.
Strong AI literacy including ethical considerations (bias, fairness, privacy, governance) and responsible AI solution deployment.
Comfortable communicating complex technical concepts in English to diverse stakeholders, and continuously updates with evolving AI technologies.