> Markdown version of [/jobs/ext/4520229-artificial-intelligence-ai-engineer](https://www.wearedevelopers.com/jobs/ext/4520229-artificial-intelligence-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). --- # Artificial Intelligence (AI) Engineer - **Company:** Robert Half - **Location:** Concord, TN, United States - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Application Performance Management, Cloud Computing, Computer Programming, Databases, Software Debugging, DevOps, Distributed Systems, Django Web Framework, Amazon DynamoDB, Python (Programming Language), PostgreSQL, MongoDB, MySQL, Node.Js, NoSQL, AI-enabled Products, Software Engineering, Systems Integration, Web Applications, Web Application Frameworks, LangChain, ReactJS, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Prompt Engineering, Backend, Git, Fastapi, Containerization, AI Platforms, AutoGen, Graphql, Front End Software Development, Asynchronous Programming, NestJS, Restful APIs, Semantic Kernel, Microservices - **Published:** November 1, 2026 - **Apply:** https://www.dice.com/job-detail/44e086fd-ab31-4e15-b980-13b586296d3a ## About the Role 7+ years of hands-on experience in software engineering with a strong record of delivering production applications. Strong programming skills in Python or Node.js, with experience building maintainable backend services and APIs. Hands-on experience developing front-end applications with React and integrating them with service-based architectures. Background working with relational and/or NoSQL databases such as PostgreSQL, MySQL, MongoDB, or DynamoDB. Demonstrated knowledge of large language models, generative AI concepts, embeddings, prompt design, and agentic workflow patterns. Experience with frameworks or platforms for AI orchestration such as LangGraph, LangChain, Semantic Kernel, AutoGen, or similar tools. Solid understanding of distributed systems, asynchronous programming, Git-based collaboration, and modern software delivery practices. Strong communication, analytical thinking, and prioritization skills, with a commitment to clean, well-documented, and maintainable code., All applicants applying for U.S. job openings must be legally authorized to work in the United States. Benefits are available to contract/temporary professionals, including medical, vision, dental, and life and disability insurance. Hired contract/temporary professionals are also eligible to enroll in our company 401(k) plan. Visit roberthalf.gobenefits.net for more information. ## Description Lead full lifecycle development of AI-enabled products, from technical planning and architecture through deployment and ongoing improvement. Design and deliver agent-based AI solutions that support reasoning, multi-step execution, tool usage, memory handling, and workflow orchestration. Build, test, and maintain scalable backend applications and services using Python frameworks such as Django, Flask, or FastAPI, or Node.js frameworks such as Express or NestJS. Create and support RESTful and GraphQL interfaces that connect web applications, internal platforms, databases, and external tools. Develop React-based user interfaces and ensure smooth interaction between front-end components and backend services. Architect microservices and distributed application patterns that improve scalability, resilience, and maintainability. Improve system efficiency by tuning application performance, refining database usage, and managing cloud resources effectively. Apply strong security practices across authentication, authorization, deployment, and production operations while supporting CI/CD pipelines and containerized environments. Establish monitoring, tracing, evaluation, and debugging practices for AI systems in production, and resolve issues across cloud-based environments. Partner with product, design, DevOps, data, and engineering teams while providing technical guidance on AI platform strategy and engineering standards.