AI Developer

Atlas Energy Solutions•Austin, TX

About The Position

The AI Developer is a technical, entry-level role within the Atlas Technology team that builds and maintains AI solutions across the business.

Bachelor’s degree (in disciplines relevant to business process improvement or technology adoption) or equivalent practical experience/training.
Programming: Foundational proficiency in one general purpose programming language (e.g. Python or C#) and one front end framework (e.g. React/JavaScript)
Comfort with REST APIs, JSON, DBs and basic data structures
Foundations: Understanding of AI/ML/LLM concepts (prompting, embeddings, retrieval) through coursework, personal projects, or internship
AI/ML/LLM concepts or project experience
Eligible to work in the U.S. without future sponsorship.
Demonstrated experience through relevant personal projects with publicly shareable artifacts (e.g., GitHub repositories, demos, technical write-ups, or case studies).

Experience building LLM-powered applications and automations
Exposure to cloud platforms and DevOps practices (Azure Functions, CI/CD pipelines, Git/GitHub, containers).
Familiarity with Microsoft tools such as Power Platform, Copilot Studio, Microsoft Foundry, Graph APIs and collaboration platforms (e.g., Teams and SharePoint)
Completion of relevant AI-focused certifications and/or accredited boot camps.

AI-powered features and applications such as conversational interfaces, workflow automations, MCP servers, and computer vision.
Connect AI solutions with Atlas internal systems, Microsoft Graph, Azure services, third-party APIs, and operational data sources.
Implement testing strategies for AI behavior including prompt evaluation, regression testing, output validation, and model performance.
Apply authentication patterns, data protection controls, and audit logging.
Ensure responsible and compliant AI usage by reinforcing approved tools, data handling, and governance guardrails; coordinate privacy/security reviews and escalate risks and exceptions as needed.
Monitor deployed solutions for performance, reliability, and cost. Respond to incidents, troubleshoot issues, and drive continuous improvement through analytics and user feedback.