> Markdown version of [/jobs/ext/1816853-ai-engineer](https://www.wearedevelopers.com/jobs/ext/1816853-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI Engineer

- **Company:** Elite
- **Location:** United States
- **Experience:** Expert
- **Salary:** $83,200.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Information Engineering, Software Debugging, Python (Programming Language), NoSQL, Regression Testing, Software Deployment, Software Engineering, Data Logging, Large Language Models, Software Troubleshooting, Fastapi, Data Lakes, Pyspark, Virtual Agents, Api Design, Data Pipelines, Databricks
- **Published:** July 23, 2026
- **Apply:** https://www.dice.com/job-detail/1bb71176-4e17-4b10-bfc4-59c4c217ddcf

## About the Role

5+ years of hands-on experience in Software Engineering, Data Engineering, and GenAI.
Strong experience with LangGraph, LangChain, Agentic AI, and production deployment of LLM solutions.
Proficiency in Python, PySpark, Databricks, Delta Lake, NoSQL, and Azure Cloud.
API development experience; FastAPI preferred.
Strong troubleshooting, problem-solving, and creative thinking skills, particularly in designing innovative solutions within the rapidly evolving Agentic AI space.
Need a creative approach for ability to solve problems with the agentic world.

## Description

Build and maintain LLM evaluation frameworks, including golden datasets, regression testing, scoring, quality thresholds, and trend tracking.
Implement observability for LLM pipelines, including logging, metrics, dashboards, alerting, latency monitoring, error tracking, and token/cost analysis.
Design and integrate AI agent tool-calling capabilities, including function calling, tool interfaces, schemas, guardrails, and structured outputs.
Develop and support scalable AI services and data pipelines while independently debugging and resolving complex technical issues.


## Related Videos

- [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure)
- [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi)
- [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data)
- [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis)
- [Agentic DevOps: How AI-Powered Automation Transforms Software Delivery on GitHub and Azure](https://www.wearedevelopers.com/videos/1539-agentic-devops-how-ai-powered-automation-transforms-software-delivery-on-github-and-azure)
- [Building and Deploying Multi-Agent Systems with ADK and Vertex AI](https://www.wearedevelopers.com/videos/1918-building-and-deploying-multi-agent-systems-with-adk-and-vertex-ai)

## Related Articles

- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care)
- [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)
- [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)