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Artificial Intelligence Engineer
Rogers, AR
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Job Description We are seeking a Mid-Level AI Engineer to build production AI applications, agents, RAG workflows, Python services, and REST APIs in partnership with senior engineers. This individual will integrate AI capabilities with enterprise APIs, databases, queues, and cloud services while developing Docker containers and deployment components. Candidates should have 7+ years of software, cloud, or AI engineering experience with strong Python fundamentals and practical knowledge of LLMs, embeddings, vector databases, RAG, and AI agents. Experience with FastAPI or Flask, automated testing, Git, logging, debugging, CI/CD, Kubernetes, and cloud platforms is preferred. The engineer will independently own assigned features or services and should have experience building core AI functionality rather than only creating APIs around an existing AI platform. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.
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7+ years of software, cloud, AI engineering, or related development experience.
Strong Python programming and software-development fundamentals.
Hands-on experience building REST APIs and backend services.
Experience with Docker, containerization, Git, automated testing, logging, debugging, and application troubleshooting.
Working knowledge of cloud services on Azure, AWS, or GCP.
Understanding of Generative AI concepts including LLMs, prompts, embeddings, RAG, and AI agents.
Ability to integrate applications with APIs, databases, messaging platforms, and other enterprise services.
Familiarity with FastAPI, Flask, or similar Python API frameworks.
Exposure to Kubernetes, CI/CD, Terraform or other infrastructure-as-code tools, serverless services, and API gateways.
Experience with LangChain, LangGraph, Semantic Kernel, vector databases, or similar AI technologies is a plus.
Ability to work across both AI and cloud engineering activities while collaborating closely with Senior AI Engineers.
Strong problem-solving skills with the ability to independently own assigned features and services.