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Data & AI Engineer

  • Indianapolis, IN, United States
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Job details

Posting language
English
Posted

Original job description

Data & AI Engineer Location: Indianapolis, IN

Summary: Develop and integrate the technical components that capture, store, process, and deliver business context to the client’s existing AI ecosystem.

Responsibilities:

  • Develop and maintain the Business Context Repository in a client approved environment, using the architecture and standards established for the project.
  • Build data integration pipelines to capture business context from approved sources, including metadata registries, catalogs, workshop outputs, BI reports, and usage information.
  • Implement structured storage and retrieval mechanisms for business definitions, ontology relationships, metadata, business rules, and ground truth datasets.
  • Integrate the repository with the client’s existing Context Injection component and relevant Graph, semantic, and metadata services.
  • Develop Python based automation to extract, transform, validate, and refresh business context.
  • Implement LLM assisted and agentic workflows for context drafting, enrichment, review, and maintenance, including human approval controls.
  • Build scheduled refresh processes, staleness detection, logging, and monitoring mechanisms.
  • Support development of the AI evaluation runner, execute technical integrations, troubleshoot failures, and maintain deployment configurations.
  • Deliver reusable source code, configuration, technical documentation, and operational runbooks to the client’s designated repositories.

Requirements

Required Technical Expertise: Python, SQL, data engineering, API integration, ETL/ELT, LLM integrations, RAG, agentic AI frameworks, structured and unstructured data processing, cloud services, CI/CD, and data governance.

More about this job

Skills

  • Databricks
  • AWS
  • Data engineering
  • Apache Spark
  • PySpark
  • SQL
  • Unity
  • Amazon Redshift
  • Identity and access management
  • CI/CD
  • Python
  • Data modelling
  • Communication skills
  • Stakeholder management
  • Mlflow
  • Microsoft Azure
  • ML

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