Senior AI Developer

Summary

Energy Transfer, recognized by Forbes as one of America's best large employers, is dedicated to responsibly and safely delivering America’s energy. We inspire employees to create superior value for customers, investors, and a sustainable future while giving back to the community through long‑standing commitments to causes such as MD Anderson Children’s Cancer Hospital, The Salvation Army, The American Red Cross, and Ronald McDonald House. We offer industry‑leading compensation, comprehensive benefits, a 401(k) match with additional profit sharing, PTO, and abundant career opportunities. Join our award‑winning, 12,000‑strong organization as we fuel the world and each other.

Technical Environment

• Core: Python, .NET, Azure Databricks (data platform)
• AI stack: Azure OpenAI, Azure AI Foundry, Azure AI Search, Microsoft Copilot Studio, Semantic Kernel, Vector Databases, Retrieval‑Augmented Generation (RAG), Semantic Search, Agentic AI, Model Context Protocol (MCP)

Essential Duties and Responsibilities

• Design, develop, deploy, and maintain AI solutions using Python and/or .NET.
• Build AI agents using Microsoft Copilot Studio or the Semantic Kernel Agent Framework.
• Build and optimize cloud‑native applications on Azure.
• Work with large‑scale data in Databricks.
• Partner with AI engineers/developers and business analysts to turn ideas and experiments into production systems.
• Apply critical thinking to evaluate model performance, troubleshoot complex issues, and improve system efficiency.
• Communicate clearly with both technical and non‑technical stakeholders.
• Prototype quickly, test rigorously, and iterate often.

Requirements

• Bachelor’s degree or equivalent experience, with relevant job experience commensurate with the selected job level.
• Professional experience building production systems with Python or .NET (proficiency in both is a strong plus).
• Strong working knowledge of cloud services and architecture patterns — Azure preferred (or equivalent experience in AWS or GCP, with willingness to ramp on Azure).
• Hands‑on experience building Retrieval‑Augmented Generation (RAG) pipelines.
• Hands‑on experience building AI agents with Microsoft Copilot Studio, Semantic Kernel Agent Framework, or an equivalent agent framework (e.g., LangGraph, AutoGen, CrewAI).
• Hands‑on experience with at least two of the following:
  • Azure AI Search (or equivalent vector/semantic search platform — Pinecone, Weaviate, pgvector, Elasticsearch with vector, AWS Kendra/OpenSearch)
  • Vector databases
  • Semantic search
  • Agentic AI systems (multi‑step reasoning, tool use, orchestration)
• Comfort working with SQL and large‑scale data platforms (Databricks experience is a plus, but the syntax is approachable if you know SQL).
• Excellent communication and critical‑thinking skills.
• Background in a smaller company or startup environment with significant ownership of technical work.
• Required experience is commensurate with the selected job level:
  • Specialist: 2‑5 years
  • Senior Specialist: 5‑8 years
  • Lead Specialist: 8+ years

Preferred Qualifications

• Proficiency in both Python and .NET.
• Direct hands‑on experience with Microsoft Copilot Studio and/or Semantic Kernel specifically.
• Hands‑on experience with Databricks specifically.
• Practical machine‑learning experience (model training, evaluation, deployment).
• Familiarity with Azure AI Foundry (or equivalent — AWS Bedrock, Google Vertex AI) and Azure OpenAI (or equivalent managed LLM service) in production.
• Experience with Model Context Protocol (MCP) or similar agent‑tooling standards.
• Natural Gas Pipeline or Energy Industry work experience is a plus.

Working Conditions

• Normal office working conditions; on‑site role, worked in person at the office 5 days per week during business hours.
• Must be able to remain in a stationary position 50% of the time due to prolonged periods of sitting or standing.
• Occasional overnight travel may be required to other business locations within the company.

Schedule

• On‑site, 5 days per week during standard business hours.
• Occasional overnight travel as needed.