AI Engineer

USEReady helps enterprises apply AI and agentic intelligence to improve decisions, automate operations, and build smarter, more autonomous business systems. For more than a decade, we have built the foundations that make this possible by modernizing BI environments, migrating legacy platforms, improving data quality, and enabling governed, cloud-first architectures. These foundations now support the next step: AI-driven insights, automated intelligence, and agent-powered decision support that reduce complexity and accelerate outcomes. We work closely with technology leaders such as AWS, Elementum, Snowflake, Tableau, Databricks, and others to help organizations modernize analytics, strengthen governance, and deploy agentic automation with confidence. Headquartered in New York City with 450+ experts across the United States, Canada, India, and Singapore, we serve industries including financial services, healthcare, manufacturing, government, education, and retail. Our deep expertise, player-coach delivery model, and focus on fast, measurable results make us a trusted partner for building an AI-ready enterprise About the Role We are looking for a talented AI Engineer with 23 years of hands-on experience in building and deploying AI/LLM-powered applications. The ideal candidate should have strong Python development skills, experience working with cloud platforms (preferably Azure), and practical exposure to LangChain and modern Generative AI frameworks. You will work on designing, developing, and deploying intelligent applications powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and cloud-native AI services. Key Responsibilities Design, develop, and maintain AI-powered applications using Python. Build and optimize RAG (Retrieval-Augmented Generation) pipelines. Develop AI agents and workflow automation using LangChain and related frameworks. Integrate LLMs such as OpenAI, Gemini, Claude, or Azure OpenAI into enterprise applications. Create APIs and backend services to support AI solutions. Deploy and manage AI applications on Azure cloud environments. Work with vector databases for semantic search and knowledge retrieval. Design prompt engineering and AI evaluation frameworks. Collaborate with business stakeholders to translate requirements into AI solutions. Monitor, troubleshoot, and optimize AI model performance in production environments. Implement best practices for security, scalability, and cost optimization. Must-Have Skills Technical Skills 2–3 years of software development experience. Strong proficiency in Python. Hands-on experience with LangChain. Experience building LLM-based applications. Experience with Azure services, preferably: Azure OpenAI Azure Functions Azure App Services Azure Storage Azure AI Services Azure Kubernetes Service (AKS) (preferred) REST API development using: FastAPI Flask Experience with vector databases such as: FAISS ChromaDB Pinecone Azure AI Search Understanding of: Prompt Engineering RAG architectures AI Agents Embeddings Semantic Search Database Skills SQL knowledge. Experience with one or more: PostgreSQL SQL Server Snowflake Version Control & DevOps Git/GitHub. CI/CD concepts. Docker fundamentals. Good-to-Have Skills Experience with multi-agent architectures. Experience with LangGraph. Knowledge of MCP (Model Context Protocol). Experience with AI evaluation frameworks. Exposure to Kubernetes. Experience with Snowflake. Understanding of MLOps practices. Knowledge of monitoring tools such as Application Insights or Azure Monitor. Preferred Qualifications Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field. AI/ML certifications are a plus. Experience working in Agile teams. What We Are Looking For Strong problem-solving skills. Ability to quickly learn new AI technologies. Excellent communication skills. Passion for Generative AI and emerging AI trends. Ability to work independently and drive solutions end-to-end