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# AI Engineer

- **Company:** ApTask
- **Location:** Plano, TX, United States
- **Experience:** Experienced
- **Salary:** $80,000.0 - $90,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Relational Databases, Github, Python (Programming Language), Machine Learning, Azure Active Directory, Search Technologies, Enterprise Data Management, Enterprise Software Applications, Large Language Models, Prompt Engineering, Software Application Programming, Generative AI, Core Api, Git, Build Management, Artificial Intelligence Markup Language (AIML), GPT, Databricks, Microservices
- **Published:** July 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=59b9207d40171fba

## About the Role

Required skills: RAG, Azure, AI, ML, LLM, * 2+ years of experience in AI/ML Engineering, Data Science, or related field

 * Experience using data from Azure Databricks or similar relational databases

 * Strong hands-on experience with Python (core development language), Git, Github; LLM frameworks especially Langchain; RAG architectures and vector search concepts

 * Experience with Azure AI ecosystem, including Azure OpenAI models and Azure AI Search

 * Understanding of AI ML concepts, LLMs, vector databases, RAG, agents

 * Familiarity with APIs, microservices, MCP and scalable system design

 * Strong communication skills

## Description

Job Summary: We are seeking an AI ML Engineer to design, develop, and deploy Generative AI applications, with a focus on Retrieval-Augmented Generation (RAG) and agentic workflows. The ideal candidate will have hands-on experience building applications using LLMs, vector databases, and agent harnesses, along with experience in Azure stack. This role involves developing scalable, production-grade AI solutions that integrate enterprise data with advanced reasoning and automation capabilities, * Design and build agentic applications using Langchain or similar, integrating enterprise data sources (Azure Databricks, documents, APIs)

 * Build and optimize RAG vector databases for use by agents using tools like Azure AI Search, or similar

 * Integrate LLMs (Azure OpenAI, GPT models) into enterprise applications with proper prompt engineering and optimization

 * Implement evaluation, monitoring, and guardrails for AI systems (accuracy, bias, hallucination control)

 * Collaborate with data engineers and application teams to integrate AI solutions into production systems


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