12 days ago
Dallas, TX, USAMid Level / Senior

Responsibilities

  • Design, build, and deploy AI-powered applications and autonomous or multi-agent workflows using large language models.
  • Build and maintain data pipelines connecting Snowflake and Azure Databricks to AI/ML workflows, including pipelines built with dbt.
  • Develop and orchestrate agentic systems using the Claude Agent SDK and Azure AI Foundry Agent Service, including tool use, RAG, and multi-step reasoning.
  • Build evaluation harnesses and testing frameworks to measure model and agent quality, reliability, and safety.
  • Prototype and evaluate emerging AI tools, models, and frameworks and recommend valuable adoption opportunities.
  • Partner with data science, data engineering, IT, and business stakeholders to turn ambiguous needs into production-ready solutions.
  • Support responsible AI practices involving data privacy, access control, and governance in Azure and Snowflake environments.

Requirements

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
  • Two to four years of hands-on experience building and shipping software, data, or AI/ML applications in production.
  • Strong proficiency in Python and experience writing tested, maintainable code.
  • Working knowledge of SQL and experience with at least one cloud data platform such as Snowflake or Databricks.
  • Hands-on experience building applications with large language models or generative AI APIs such as Claude, OpenAI, or Azure OpenAI.
  • Familiarity with version control, testing, CI/CD, and common software design patterns.
  • Strong problem-solving and communication skills with the ability to collaborate across technical and business teams.
  • Ability to learn new tools, frameworks, and platforms quickly and work effectively in an ambiguous, fast-evolving environment.
  • Preferred experience with Azure services, especially Azure Databricks and Azure AI Foundry.
  • Preferred experience with Anthropic Claude, the Claude Agent SDK, or comparable agent development frameworks.
  • Preferred experience with vector databases, embedding and chunking strategies, unstructured-data conversion, dbt, MCP, infrastructure-as-code, containerization, or cloud deployment.
  • Exposure to the energy industry, contributions to open-source or personal AI projects, or participation in the AI developer community is preferred.

Tech Stack

AzureDatabricksdbtGitPythonSnowflakeSQL

Categories

AI ApplicationsData Engineering
Diamondback Energy

About Diamondback Energy

1,001-5,000 employees
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