{"schemaVersion":"jobsearcher.job.v1","id":"e1ba022d09f3b32ea2aa5bb4","url":"https://jobsearcher.com/jobs/e1ba022d09f3b32ea2aa5bb4","canonicalUrl":"https://jobsearcher.com/jobs/e1ba022d09f3b32ea2aa5bb4","title":"AI Engineer","description":"SkillsetDatabricks\r\nPython (pandas, scikit-learn, NumPy, TensorFlow, MLflow)\r\nSQL\r\nAgentic AI frameworks (LangChain, LangGraph, OpenAI, MCP)\r\nResponsibilitiesDevelop machine learning, deep learning, and generative AI models to support RCM use cases such as claim outcome prediction, denials classification, next best action recommendation, clinical appeal summarization, and workflow optimization.\r\nBuild end to end ML pipelines including feature engineering, model training, hyperparameter tuning, validation, and monitoring.\r\nResearch and apply advanced techniques in LLMs, embeddings, retrieval augmentation (RAG), prompt engineering, and document intelligence.\r\nTranslate operational and product requirements into measurable model objectives, data specifications, and evaluation frameworks.\r\nConduct exploratory data analysis (EDA) to understand data patterns, anomalies, and business insights.\r\nImplement and follow best practices around MLOps, including model versioning, reproducibility, feature stores, and drift monitoring.\r\nPartner with Data Engineers to ensure feature availability, data quality, and scalable ML/AI deployment within Azure Databricks and enterprise platforms.\r\nCollaborate with cross-functional teams to communicate insights, present model results, and drive adoption of ML solutions.\r\nMaintain awareness of emerging AI technologies and propose enhancements or new opportunities for Provider Engineering platforms.\r\nRequired QualificationsBachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.\r\n3-7+ years of hands‑on experience developing ML or AI models in an applied industry setting (healthcare experience strongly preferred).\r\nStrong proficiency in: Databricks Python (pandas, scikit-learn, NumPy, TensorFlow, MLflow) SQL\r\nPreferredKnowledge of US healthcare, ideally with Revenue Cycle Management (RCM) experience, including familiarity with EDI transactions such as 837 and 835.\r\nAdditional RequirementsAbility to thrive in a fast-paced environment with rapid prototyping, ambiguity, and iterative delivery.\r\nStrong working knowledge of GitHub Copilot (or equivalent enterprise‑approved AI coding assistant) to accelerate development.\r\nSelf‑motivated and solution‑oriented; able to independently research, troubleshoot, and identify paths forward when facing technical or data challenges.\r\nExperience working in Azure or similar cloud environments: Azure Databricks (MLflow, Delta Lake), Azure Machine Learning, Azure Data Lake / Azure Data Factory (in partnership with Data Engineering).\r\nHands‑on experience in at least one of the following: Classification, regression, time series, or recommendation systems.\r\nAgentic AI / Large Language Models (LLMs) / RAG experience.\r\nStrong statistical modeling foundation and experience building production-quality ML systems.\r\nAbility to communicate technical findings to nontechnical stakeholders clearly and effectively.#J-18808-Ljbffr","company":"Shrive Technologies","rawCompany":"shrive technologies","city":"Austin","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-11-04T02:23:12.252Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"AI Engineer","description":"SkillsetDatabricks\r\nPython (pandas, scikit-learn, NumPy, TensorFlow, MLflow)\r\nSQL\r\nAgentic AI frameworks (LangChain, LangGraph, OpenAI, MCP)\r\nResponsibilitiesDevelop machine learning, deep learning, and generative AI models to support RCM use cases such as claim outcome prediction, denials classification, next best action recommendation, clinical appeal summarization, and workflow optimization.\r\nBuild end to end ML pipelines including feature engineering, model training, hyperparameter tuning, validation, and monitoring.\r\nResearch and apply advanced techniques in LLMs, embeddings, retrieval augmentation (RAG), prompt engineering, and document intelligence.\r\nTranslate operational and product requirements into measurable model objectives, data specifications, and evaluation frameworks.\r\nConduct exploratory data analysis (EDA) to understand data patterns, anomalies, and business insights.\r\nImplement and follow best practices around MLOps, including model versioning, reproducibility, feature stores, and drift monitoring.\r\nPartner with Data Engineers to ensure feature availability, data quality, and scalable ML/AI deployment within Azure Databricks and enterprise platforms.\r\nCollaborate with cross-functional teams to communicate insights, present model results, and drive adoption of ML solutions.\r\nMaintain awareness of emerging AI technologies and propose enhancements or new opportunities for Provider Engineering platforms.\r\nRequired QualificationsBachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.\r\n3-7+ years of hands‑on experience developing ML or AI models in an applied industry setting (healthcare experience strongly preferred).\r\nStrong proficiency in: Databricks Python (pandas, scikit-learn, NumPy, TensorFlow, MLflow) SQL\r\nPreferredKnowledge of US healthcare, ideally with Revenue Cycle Management (RCM) experience, including familiarity with EDI transactions such as 837 and 835.\r\nAdditional RequirementsAbility to thrive in a fast-paced environment with rapid prototyping, ambiguity, and iterative delivery.\r\nStrong working knowledge of GitHub Copilot (or equivalent enterprise‑approved AI coding assistant) to accelerate development.\r\nSelf‑motivated and solution‑oriented; able to independently research, troubleshoot, and identify paths forward when facing technical or data challenges.\r\nExperience working in Azure or similar cloud environments: Azure Databricks (MLflow, Delta Lake), Azure Machine Learning, Azure Data Lake / Azure Data Factory (in partnership with Data Engineering).\r\nHands‑on experience in at least one of the following: Classification, regression, time series, or recommendation systems.\r\nAgentic AI / Large Language Models (LLMs) / RAG experience.\r\nStrong statistical modeling foundation and experience building production-quality ML systems.\r\nAbility to communicate technical findings to nontechnical stakeholders clearly and effectively.#J-18808-Ljbffr","datePosted":"2026-11-04T02:23:12.252Z","dateModified":"2026-11-04T02:23:12.252Z","hiringOrganization":{"@type":"Organization","name":"Shrive Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"e1ba022d09f3b32ea2aa5bb4"},"url":"https://jobsearcher.com/jobs/e1ba022d09f3b32ea2aa5bb4"}}