AI Engineer

Crescent Energy•Houston, TX

About The Position

Crescent is a differentiated U.S. energy company committed to delivering value through a disciplined, returns-driven growth through acquisition strategy and consistent return of capital. Our long-life, balanced portfolio combines stable cash flows from low-decline production with a deep, high-quality development inventory. Crescent is a top three producer (by gross operated production) in the Eagle Ford basin. Crescent’s leadership is an experienced team of investment, financial and industry professionals that combines proven investment and operating expertise. For more than a decade, Crescent and our predecessors have executed on a consistent strategy focused on cash flow, risk management and returns. Through disciplined and accretive investments, we have successfully tripled the size of our company since going public in December 2021 while maintaining a strong balance sheet. We are seeking an experienced Senior AI Platform Developer to take ownership of the Crescent AI (CAI) platform - our enterprise-grade conversational AI system that powers multiple specialized bots for different business functions. This is a hands-on technical role that combines cutting-edge AI/ML development with enterprise integration and business stakeholder engagement. Technology Stack: Backend: Python 3.10+, FastAPI, Async/Await patterns AI/ML: Azure OpenAI (GPT-5), prompt engineering, RAG patterns Frontend: Vanilla JavaScript, MSAL.js authentication, Server-Sent Events Databases: Snowflake, SQL Server, Azure Cosmos DB Search: Azure AI Search with semantic ranking Infrastructure: Ubuntu Linux, Nginx, Docker, Systemd Cloud: Azure (OpenAI, Cosmos DB, Blob Storage, AI Search) Auth: Azure AD with OAuth 2.0/OIDC

Requirements

5+ years of Python development with strong async/await experience
2+ years working with LLMs (GPT-4, Claude, etc.) and prompt engineering
Production experience with FastAPI or similar async frameworks
SQL expertise including complex queries and database design
Cloud platforms - Azure preferred, AWS/GCP acceptable
Linux/Unix administration and shell scripting
Git version control and collaborative development
Natural Language Processing: Understanding of embeddings, RAG, semantic search
Streaming architectures: SSE, WebSockets, async generators
Authentication: OAuth 2.0, JWT tokens, session management
Database systems: Both SQL and NoSQL paradigms
RESTful APIs: Design, implementation, and consumption
Infrastructure as Code: Docker, systemd services, nginx configuration

Nice To Haves

Snowflake or similar cloud data warehouse
Azure AI Search or Elasticsearch
Cosmos DB or similar NoSQL databases
MSAL.js or similar authentication libraries
Markdown processing and rendering
Document generation (PDF, DOCX, XLSX)
Experience with ChromaDB or vector databases
Knowledge of HSE (Health, Safety, Environment) regulations
Financial services or energy sector experience
Contributions to open-source AI/ML projects
Experience with multi-modal AI (images, documents)
Background in building conversational AI systems

Responsibilities

Platform Development & Maintenance (40%) Maintain and enhance the existing AI platform Implement bug fixes and performance optimizations Ensure 99.9% uptime for production services Manage streaming responses, conversation history, and document exports Handle natural language to SQL generation for database queries Maintain authentication flow with Azure AD and token management
New Bot Development (30%) Work with business stakeholders to identify AI automation opportunities Design and implement new specialized bots following established patterns Create intelligent system prompts with context injection Integrate with enterprise data sources (databases, APIs, documents) Implement RAG (Retrieval-Augmented Generation) patterns Build natural language interfaces for complex business queries
Business Partnership (20%) Meet with department heads to understand pain points Translate business requirements into technical solutions Demo capabilities and gather feedback Create documentation for end users Provide training and support for new features Measure and report on bot usage and value delivered
Technical Excellence (10%) Optimize Azure OpenAI token usage and costs Improve response accuracy and relevance Enhance error handling and user experience Document code changes and architectural decisions Participate in code reviews and knowledge sharing Stay current with AI/ML best practices

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