Senior GenAI Engineer – LangGraph UI, LangFlow & Python

Job Title: Senior GenAI Engineer – LangGraph UI, LangFlow & Python ( 2 positions) Location: Irving TX (Onsite – 3 days @ office) Duration: 12 months Job Description: We are seeking a highly skilled Senior GenAI Engineer with proven expertise in developing enterprise-level AI agentic solutions that can handle high-volume, complex data processing. The ideal candidate will have hands-on experience with LangGraph UI, LangFlow, and Python, building robust agentic AI workflows and integrating them with enterprise systems. Key Responsibilities: • Design, develop, and deploy AI agentic architectures for enterprise-scale solutions. • Build, orchestrate, and optimize LangGraph UI and LangFlow pipelines for dynamic AI workflows. • Leverage Python to implement data processing, integration, and automation logic. • Handle high-volume and real-time data streams, ensuring scalability and performance. • Collaborate with product teams, data engineers, and business stakeholders to align AI workflows with enterprise use cases. • Implement monitoring, observability, and failover strategies for agentic AI systems. • Research and integrate emerging GenAI frameworks, LLMs, and vector databases into enterprise solutions. Required Skills & Experience: • Strong hands-on experience with LangGraph UI and LangFlow for building agentic AI workflows. • Proficiency in Python (FastAPI, asyncio, Pandas, etc.) for data-intensive applications. • Experience in designing solutions that handle large-scale, high-volume data processing. • Deep understanding of LLMs (OpenAI, Anthropic, Llama, etc.) and how to orchestrate them into multi-agent workflows. • Knowledge of enterprise data integration, APIs, and cloud platforms (AWS, Azure, or GCP). • Strong problem-solving skills with the ability to design scalable and fault-tolerant AI systems. Preferred Skills: • Experience with vector databases (Pinecone, Weaviate, FAISS, Chroma). • Exposure to RAG (Retrieval-Augmented Generation) pipelines. • Familiarity with Kubernetes, Docker, and CI/CD for deploying AI solutions. • Knowledge of data security, compliance, and governance in enterprise AI.