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Energy Transfer Partners

Principal AI Developer

Energy Transfer Partners
Houston, TX Full time Posted 4h ago
Backend Developer Agentic Ai Ai Agent Ai Agent Platform Ai Security Artificial Intelligence Artificial Intelligence Engineer Azure Ai Cloud Operations Data Analysis Data Analytics Data Architecture Data Engineer Data Pipeline Data Platform Data Processing Databases DevOps Engineer Engineering Generative AI Programming Project Management Software Engineering Vector Databases
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Job Description

Energy Transfer Partners is seeking a hands-on Principal AI Developer to help design, build, deploy, and continuously improve production AI solutions within its Enterprise AI team. The position combines end-to-end development across AI systems, cloud-native tooling, and large-scale data platforms, with close collaboration across technical and business partners.

Role Overview

In this on-site role based in Houston, TX, you will work with AI engineers and business analysts to move ideas and experiments into production systems. The work includes building production-grade AI applications, evaluating model and system performance, and iterating on efficiency and reliability.

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.
  • Create and optimize cloud-native applications on Azure.
  • Work with large-scale data in Databricks.
  • Collaborate with AI engineers/developers and business analysts to convert concepts 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 frequently.

Required Qualifications

  • 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, with Azure preferred (or equivalent experience in AWS or GCP, plus 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 (for example: LangGraph, AutoGen, CrewAI).
  • Hands-on experience with at least two of: Azure AI Search (or equivalent vector/semantic search platforms such as Pinecone, Weaviate, pgvector, Elasticsearch with vector, AWS Kendra/OpenSearch).
  • Hands-on experience with at least two of: Vector databases.
  • Hands-on experience with at least two of: Semantic search.
  • Hands-on experience with at least two of: Agentic AI systems (multi-step reasoning, tool use, orchestration).
  • Comfort working with SQL and large-scale data platforms (Databricks experience is a plus if SQL syntax is understood).
  • Excellent communication and critical-thinking skills.
  • Background in a smaller company or startup environment with significant ownership of technical work.

Technology Stack

Key technologies include Python, .NET, Azure, Databricks, Azure OpenAI, Azure AI Foundry, and Azure AI Search. The role also involves Microsoft Copilot Studio, Semantic Kernel, RAG (Retrieval-Augmented Generation), Semantic Search, Agentic AI, MCP (Model Context Protocol), and supporting frameworks and platforms such as LangGraph, AutoGen, CrewAI, Pinecone, Weaviate, pgvector, and Elasticsearch, along with AWS Kendra and OpenSearch and SQL.

Benefits

  • 401(k) match with additional profit sharing
  • PTO
  • Industry leading compensation
  • Comprehensive benefits
  • Abundant career opportunities

Preferred Qualifications

  • Proficiency in both Python and .NET.
  • Direct hands-on experience with Microsoft Copilot Studio and/or Semantic Kernel.
  • Hands-on experience with Databricks.
  • Practical ML experience (model training, evaluation, deployment).
  • Familiarity with Azure AI Foundry (or equivalent such as AWS Bedrock or 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

  • Usually 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.

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