$117,800–$212,500
AI Developer
First seen · open on Workday as of
Pay not postedDallas, TXFull-time
Design, build, and deploy AI-powered applications and autonomous/multi-agent workflows using LLMs (Claude, Azure OpenAI).
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At a glance
Posted base pay
Not posted
Median $149K
Mid-level FDE postings106 postings · middle 50% of posted pay$123K–$162KThe work
Builds for teams inside the company
Balance Mostly building
Project stages
- Pre-sales (not covered)
- Proof of concept
- Implementation
- Operations
- Coding
- Writes production code
- Builds for
- Internal teams
- Level
- Mid
- Role
- Individual contributor
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The job description from Diamondback Energy
CURRENT EMPLOYEES - Please apply using "Jobs Hub" in Workday. This career site is for external applicants only.
The AI Developer is a foundational member of Diamondback Energy's new AI team, responsible for building and deploying AI-powered applications, agents, and workflows that turn emerging AI capabilities into practical business value. Working across Microsoft Azure (including Azure Databricks and Azure AI Foundry), Snowflake, and Anthropic's Claude and Claude Agent SDK, the AI Developer will prototype, build, and productionize solutions spanning generative AI, agentic workflows, and applied machine learning. This role is intentionally broad: the ideal candidate brings a range of technical exposure, a strong foundation in software and data engineering, and — above all — genuine enthusiasm for learning new tools and approaches as the field evolves.
Job Responsibilities
Include but are not limited to
- Design, build, and deploy AI-powered applications and autonomous/multi-agent workflows using large language models (Claude, Azure OpenAI models via Azure AI Foundry, and others)
- Build and maintain data pipelines connecting Snowflake and Azure Databricks to AI/ML workflows (using tools such as dbt), ensuring models and agents operate on trusted, well-structured data
- Develop and orchestrate agentic systems using the Claude Agent SDK and Azure AI Foundry Agent Service, including tool use, retrieval-augmented generation (RAG), and multi-step reasoning
- Build evaluation harnesses and testing frameworks to measure model and agent quality, reliability, and safety before and after deployment
- Rapidly prototype and evaluate emerging AI tools, models, and frameworks; recommend adoption where they add clear value
- Partner with data science, data engineering, IT, and business stakeholders to translate ambiguous needs into working, production-ready solutions
- Support responsible AI practices, including data privacy, access control, and governance, within Azure and Snowflake environments
Required Qualifications
- Bachelor's Degree in Computer Science, Data Science, Engineering, Mathematics, or a related field
- Two (2) to four (4) years of hands-on experience building and shipping software, data, or AI/ML applications in production
- Strong proficiency in Python, with experience writing tested, maintainable code
- Working knowledge of SQL and experience with at least one cloud data platform (e.g., Snowflake, Databricks, or similar)
- Hands-on exposure to building applications with large language models or generative AI APIs (e.g., Claude, OpenAI, Azure OpenAI, or similar)
- Familiarity with software engineering fundamentals: version control (Git/GitHub), testing, CI/CD, and common design patterns
- Strong problem-solving and communication skills, with the ability to work effectively across data science, engineering, and business teams
- A demonstrated pattern of self-directed learning — picking up new tools, frameworks, and platforms quickly and enthusiastically
- Comfort operating with ambiguity in a fast-evolving field, including a new team, evolving tools, and undefined processes
Preferred Qualifications
- Direct experience with Microsoft Azure services, particularly Azure Databricks and Azure AI Foundry
- Direct experience with Anthropic Claude, the Claude Agent SDK, or comparable agent development frameworks
- Experience with vector databases and embedding/chunking strategies for retrieval and semantic search
- Experience converting unstructured data (documents, PDFs, emails, images, etc.) into structured, queryable formats for AI/ML use
- Experience with dbt (data build tool) for building, testing, and documenting data transformation pipelines
- Familiarity with the Model Context Protocol (MCP) or other tool-calling / agent orchestration patterns
- Experience with infrastructure-as-code, containerization, or cloud deployment practices
- Exposure to the energy industry or other data- and asset-intensive industries
- Contributions to open-source AI projects, personal AI projects, or active participation in the broader AI developer community
Diamondback is an Equal Employment Opportunity Employer. Diamondback provides equal employment opportunities to all qualified applicants without regard to race, sex, sexual orientation, gender identity, national origin, color, age, religion, veteran or disability status, genetic information, pregnancy, or any other status protected by law. Diamondback participates in E-Verify. Learn more about E-Verify.
View posting at Diamondback Energy
About Diamondback Energy
Diamondback develops and operates unconventional oil and natural gas reserves in the Permian Basin, with integrated gathering and midstream assets.
Public · 1000–2000 people
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