AI/Data Engineer :: Remote :: Hot Requirement

Position Name : AI/Data Engineer Location: Remote Position Type: W2/Fulltime Work authorization: Any work authorization can apply for these openings. Education- Required a Bachelor Degree And Equivalent My name is Smriti Singh and I am a Staffing Specialist at HYR GLOBAL SOURCE INC. I am reaching out to you on an exciting job opportunity with one of our clients.

• We are seeking an experienced Agentic AI Engineer with a strong background in AI engineering, data engineering, and enterprise application integration. The ideal candidate will have hands-on experience developing AI-powered applications using Large Language Models (LLMs), agent frameworks, Retrieval-Augmented Generation (RAG), and vector databases.
• In this role, you will help design, develop, and integrate AI agents into existing integration, fleet management, and telematics connectivity products. You will work closely with Technical Product Managers and cross-functional engineering teams to identify AI opportunities, build intelligent solutions, and deliver scalable, production-ready AI capabilities.
• This is an opportunity to take ownership of AI engineering initiatives as the first dedicated AI developer on the team, helping establish AI development practices and supporting the organization’s long-term AI strategy.
• Key Responsibilities
• Design, develop, and deploy AI agents and agentic workflows using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or Semantic Kernel.
• Integrate LLMs from providers such as OpenAI, Azure OpenAI, Anthropic, or other suitable model platforms into enterprise applications.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for context-aware information retrieval and response generation.
• Implement vector search and embedding-based retrieval using vector databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS.
• Design and develop AI-powered features for integration platforms, fleet management solutions, and telematics connectivity products.
• Build APIs, microservices, and integration components to connect AI agents with existing applications, enterprise systems, and data sources.
• Develop data pipelines and data processing workflows to prepare, transform, and deliver high-quality data for AI applications.
• Integrate structured and unstructured data sources to support retrieval, knowledge management, and AI-driven decision-making.
• Apply prompt engineering, context management, tool calling, and agent orchestration techniques to improve AI application performance.
• Implement evaluation, testing, monitoring, logging, and error-handling mechanisms to ensure reliable and secure AI solutions.
• Collaborate with Technical Product Managers and business stakeholders to translate requirements into technical designs and deliver working solutions independently.
• Communicate technical concepts, implementation approaches, risks, and recommendations to both technical and non-technical audiences.
• Establish reusable AI development patterns, technical standards, documentation, and best practices for future AI initiatives.
• Stay current with emerging developments in Agentic AI, LLMs, data engineering, and enterprise AI integration.
• Required Skills and Qualifications
• Strong programming experience in Python and software application development.
• Hands-on experience building LLM-powered applications and AI agents.
• Experience with one or more agent frameworks, such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or Semantic Kernel.
• Strong understanding of LLM integration, prompt engineering, tool calling, function calling, and agent orchestration.
• Practical experience implementing RAG architectures, embedding generation, semantic search, and retrieval pipelines.
• Experience working with vector databases or vector search technologies such as Pinecone, Weaviate, Chroma, Milvus, or FAISS.
• Solid understanding of data engineering concepts, including ETL/ELT, data transformation, data pipelines, and data quality.
• Experience designing and consuming REST APIs and integrating AI capabilities into existing applications and services.
• Knowledge of SQL, structured and unstructured data, and data preparation for AI/ML applications.
• Understanding of cloud-based AI deployment, application security, scalability, and production support.
• Ability to work independently, manage technical tasks end-to-end, and collaborate effectively with product and engineering …