> Markdown version of [/jobs/ext/3783815-ai-engineer](https://www.wearedevelopers.com/jobs/ext/3783815-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:** VDart, Inc. - **Location:** Chicago, IL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Business Software, Computer Programming, Continuous Integration, Data Cleansing, Software Debugging, Information Retrieval, Python (Programming Language), Machine Learning, Performance Tuning, Inference Optimization, OpenAI, Tensorflow, Search Technologies, Software Deployment, SQL Databases, Systems Integration, Unstructured Data, Pinecone, Data Processing, Google Cloud, Enterprise Software Applications, Feature Engineering, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Google Vertex AI, Model Validation, Llamaindex, Generative AI, Agentic-AI, Git, AI Platforms, Scikit Learn, Kubernetes, Information Technology, Weaviate, Milvus, Machine Learning Operations, FAISS, Restful APIs, Data Pipelines, Docker, Microservices - **Published:** October 16, 2026 - **Apply:** https://www.careerjet.com/jobad/us402bd69dd82684b0263aea2ce5536768 ## About the Role Strong programming experience in Python. Hands-on experience with Machine Learning and Generative AI. Experience working with LLMs, prompt engineering, and RAG architectures. Knowledge of AI/ML frameworks such as PyTorch, TensorFlow, or Scikit-learn. Experience with LangChain, LlamaIndex, or similar AI application frameworks. Understanding of embeddings, vector databases, semantic search, and information retrieval. Experience developing REST APIs and integrating AI models into applications. Strong knowledge of data processing, SQL, and data pipeline development. Experience with Git, testing, debugging, and production deployment practices. Preferred Skills Experience with agentic AI, AI agents, and multi-agent workflows. Knowledge of vector databases such as Pinecone, FAISS, Weaviate, or Milvus. Experience with cloud AI services such as AWS Bedrock, Azure OpenAI, or Google Vertex AI. Familiarity with Docker, Kubernetes, CI/CD, and MLOps. Experience with model fine-tuning, model evaluation, and inference optimization. Knowledge of responsible AI, model governance, and AI security. Education Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field, or equivalent practical experience ## Description We are seeking an experienced AI Engineer to design, develop, and deploy AI-powered applications using machine learning, Generative AI, Large Language Models (LLMs), and cloud-based AI services. The ideal candidate will have strong Python programming skills, hands-on experience building production-ready AI solutions, and expertise in integrating AI models into enterprise applications. Key Responsibilities Design, develop, and deploy AI and machine learning solutions for business applications. Build Generative AI applications using LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and vector databases. Develop AI agents and intelligent automation workflows to solve complex business problems. Build data pipelines for data preparation, feature engineering, model training, and evaluation. Integrate AI models with enterprise applications through REST APIs and microservices. Implement model evaluation, monitoring, performance optimization, and responsible AI practices. Work with structured and unstructured data to develop scalable AI solutions. Deploy and manage AI applications using AWS, Azure, or Google Cloud. Collaborate with data scientists, software engineers, architects, and business stakeholders. Maintain technical documentation and follow security, governance, and data privacy standards. Required Skills