Atlas Energy Solutions
AI Developer
About this role
Atlas Energy Solutions seeks an entry-level AI Developer to build and deploy AI-powered solutions across the organization, including conversational interfaces, automations, and computer vision applications. You'll integrate AI with internal systems and Azure services while ensuring responsible governance, security, and performance monitoring.
What you'll do
- Develop AI features including conversational interfaces, workflow automations, MCP servers, and computer vision applications
- Integrate AI solutions with internal systems, Microsoft Graph, Azure services, and third-party APIs
- Design and implement testing strategies for AI behavior, prompt evaluation, and model performance
- Apply authentication, data protection controls, and audit logging to AI solutions
- Enforce responsible AI governance, data handling policies, and coordinate security reviews
- Monitor deployed solutions for performance and reliability; troubleshoot issues and gather user feedback
What they're looking for
- Python or C# programming
- React or JavaScript front-end framework
- REST APIs, JSON, databases, and data structures
- AI/ML/LLM concepts (prompting, embeddings, retrieval)
- Azure cloud platform and DevOps practices
- Microsoft tools (Power Platform, Copilot Studio, Graph APIs)
- Git/GitHub version control
- CI/CD pipelines and containerization
Benefits
- Great Place to Work certification
- Top Place to Work For recognition in Austin
- Veteran-friendly hiring practices
- Opportunity to work with cutting-edge AI technology
- Collaborative team environment
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Atlas Energy Solutions
Atlas Energy Solutions operates energy production infrastructure in the Permian Basin with a focus on technology-driven operations and automation. The company is hiring for leadership roles in network engineering and infrastructure management, as well as AI developers to build intelligent solutions integrated with their internal systems.
- Website
- atlasesolutions.com
Likely interview questions
- Walk us through a personal AI/LLM project you've built. What was the challenge, what tools did you use, and how did you test the AI's behavior?
- Describe your experience with prompt engineering and embeddings. How have you optimized prompts or retrieval methods in a project?