Overview
On Site
60k - 90k
Full Time
Skills
Energy
Recruiting
Marketing Analytics
Ideation
Evaluation
Regulatory Compliance
Collaboration
Data Science
LangChain
Autogen
Prompt Engineering
Management
Use Cases
Artificial Intelligence
Python
API
Cloud Computing
Amazon Web Services
Google Cloud Platform
Google Cloud
Microsoft Azure
Machine Learning Operations (ML Ops)
Workflow
Job Details
We are a leading utilities and energy company with operations across nearly every state in the contiguous U.S. We generate, distribute, and deliver power to millions-and now we're investing deeply in AI, LLMs, and next-generation data science to power our future.
Our AI & Data Science group is building an internal team focused on Agentic AI-real-world implementations of intelligent agents that augment internal teams across marketing, analytics, operations, and more. This team owns the full AI agent lifecycle: from ideation and design to deployment and governance.
We're hiring two AI Engineers to join this group.
What You'll Do
Our AI & Data Science group is building an internal team focused on Agentic AI-real-world implementations of intelligent agents that augment internal teams across marketing, analytics, operations, and more. This team owns the full AI agent lifecycle: from ideation and design to deployment and governance.
We're hiring two AI Engineers to join this group.
What You'll Do
- Build and implement AI agents for internal teams (e.g., chatbot for Marketing, analytics support agents, etc.)
- Work across the entire lifecycle: ideation, framework design, prompt engineering, evaluation, deployment, and governance
- Develop and manage prompt libraries for scalable use across departments
- Design strategies to mitigate hallucinations and ensure LLM reliability in enterprise settings
- Contribute to AI governance protocols, ensuring compliance, fairness, and safety
- Integrate APIs and LLMs into internal tools using Python
- Collaborate with cross-functional teams including Data Science, IT, and business stakeholders
- Experience designing or implementing AI agents or autonomous systems
- Familiarity with agent frameworks (e.g., LangChain, CrewAI, AutoGen, etc.)
- Strong experience in prompt engineering and prompt library management
- Understanding of AI hallucinations and approaches to mitigate them in real-world use cases
- Exposure to AI governance-especially around model behavior, bias, and usage policy
- Proficiency in Python (both API integration and application-level development)
- Hands-on experience with LLMs such as GPT-4, Claude, Gemini, or similar
- Bonus: Familiarity with cloud platforms (AWS, Google Cloud Platform, Azure) and MLOps workflows
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