Principal AI Developer

Energy Transfer Family of Partnerships; Houston (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

PTO

401(k) match

Profit sharing

Job summary

Energy Transfer is seeking a hands-on AI Developer to join our Enterprise AI team in Houston. You will design, prototype, build, and deploy AI solutions using Python and/or .NET on Azure, working with Databricks and a range of AI tooling.

The ideal candidate has strong production experience, cloud know‑how, and a track record of delivering real systems in fast‑moving environments. This on‑site role offers growth, PTO, and robust benefits.

Qualifications

• Bachelor’s degree or equivalent experience, with relevant job experience commensurate with the selected job level (see below).
• 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 RAG (Retrieval‑Augmented Generation) 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, Vector databases, Semantic search, Agentic AI systems.
• 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.

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.

Skills

Python

C# / .NET

Azure

Databricks

AI/ML concepts

SQL

Communication

Education

Bachelor’s degree or equivalent experience

Tools

Microsoft Copilot Studio

Semantic Kernel

Databricks

LangGraph

AutoGen

CrewAI

Pinecone

Weaviate

Elasticsearch

Job description

Energy Transfer, recognized by Forbes as one of America’s best large employers, is dedicated to responsibly and safely delivering America’s energy. We are driven to inspire our employees to create superior value for our customers, our investors, a sustainable future and giving back to the community where we have long-standing commitments to causes including MD Anderson Children’s Cancer Hospital, The Salvation Army, The American Red Cross, Ronald McDonald House and many more.

We value all of our employees who make our growth and success possible. We are proud to offer industry leading compensation, comprehensive benefits, 401(k) match with additional profit sharing, PTO and abundant career opportunities.

Come join our award winning over 12,000 strong organization as we fuel the world and each other!

++Summary:++

Energy Transfer is looking for a hands‑on AI Developer with strong expertise in Python or .NET, cloud platforms, and modern data tooling to join our multidisciplinary Enterprise AI team. This developer will work alongside AI engineers/developers and business analysts to build, ship, and iterate on real production AI solutions.

This role is ideal for someone who thrives in a fast‑paced environment where they own work end‑to‑end: prototyping, building, deploying, and refining. Candidates who have come up through a smaller company or startup environment — wearing multiple hats and shipping real systems — will feel right at home.

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 · RAG (Retrieval‑Augmented Generation) · Semantic Search · Agentic AI · MCP (Model Context Protocol)

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: Education and/or Experience, Knowledge, Skills & Abilities

To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily. The requirements for this position are listed below:

• Bachelor’s degree or equivalent experience, with relevant job experience commensurate with the selected job level (see below).
• 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 RAG (Retrieval‑Augmented Generation) 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:

• The Senior Specialist level requires a Bachelor’s degree or equivalent experience and 5‑8 years of relevant job related experience.
• The Lead Specialist level requires a Bachelor’s degree or equivalent experience and 8+ years of relevant job related experience.
• The Principal Specialist level requires a Bachelor’s degree or equivalent experience and 10+ years of relevant job related experience.

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 ML 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 MCP (Model Context Protocol) or similar agent‑tooling standards.
• Natural Gas Pipeline or Energy Industry work experience is a plus.

Working Conditions

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.

• Usually, normal office working conditions.
• This is an 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.