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# AI Engineer

- **Company:** Everforth Apex
- **Location:** Conroe, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Data Governance, Python (Programming Language), Rapid Prototyping Process, Software Deployment, Cloud Platform System, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Restful APIs, Databricks
- **Published:** June 4, 2026
- **Apply:** https://www.dice.com/job-detail/7bc6e95f-e08c-4590-8753-b2273ee0ac3e

## About the Role

An undergraduate degree in STEM with 5+ years in software or related domain, featuring 2+ years specialized in AI/ML, LLM solutions, and hands-on development of agentic systems.

Strong proficiency in Python, REST APIs, prompt engineering, RAG pipelines, and agent orchestration, with experience using LangGraph (or similar) for stateful, tool-driven execution.

Experience deploying and operating LLM/agent workflows in production, including monitoring and evaluation.

Working knowledge of Azure based cloud environments, including Azure AI Foundry and Databricks, in enterprise settings.

Self-directed learner with strong problem-solving skills and practical business judgment.

## Description

As a Senior AI Engineer, you will design and ship agentic systems that make redesigned workflows real. This role is not about optimizing what already exists-you will build AI-native processes from the ground up, translating business intent into production-grade systems.

This is a high-ownership, hands-on role. You will prototype rapidly, validate with domain experts, and deploy incrementally. We are looking for someone deeply passionate about AI who stays current by choice and can innovate quickly within established governance, security, and data guardrails.

Job Duties

Design, build, and deploy end-to-end, multi-step agentic AI systems that replace or reimagine DBS business workflows.

Architect agent pipelines using tool-calling, memory, retrieval-augmented generation, and orchestration patterns appropriate to workflow risk and complexity.

Implement human-in-the-loop and escalation mechanisms for high-risk or low-confidence decisions.

Integrate agentic systems with enterprise data sources, internal APIs, and third-party tools in compliance with security and data governance policies.

Ensure strong data grounding, output quality, reliability, and graceful failure behavior in production systems.

Select appropriate GenAI frameworks and manage LLM integrations, prompts, and model versions.

Own delivery end-to-end from rapid prototype through pilot and production deployment.

Work closely with process owners, domain experts, and governance partners to deliver trusted, usable solutions.


## 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)
- [Developer Tools for Microsoft Azure](https://www.wearedevelopers.com/videos/450-developer-tools-for-microsoft-azure)
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- [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source)
- [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more)
- [AI for Enterprise Developers - Dr. Damir Dobric](https://www.wearedevelopers.com/videos/1831-ai-for-enterprise-developers-dr-damir-dobric)

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- [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)