G

Senior AI / GenAI Engineeri in GA/ NY (Hybrid 3 days)

Georgia IT Inc
2 hours ago
Full-time
On-site
New York, United States
Senior AI / GenAI Engineer

Candidates must have experience delivering enterprise AI solutions in production environments, not only POC or personal projects/educational projects. We are seeking a Senior AI / GenAI Engineer with strong experience in machine learning, generative AI, and enterprise-scale AI platform development. The ideal candidate should have hands-on experience building production-grade AI systems, including Retrieval-Augmented Generation (RAG) platforms, vector search pipelines, autonomous AI agents, and scalable ML model deployment. The role requires expertise in Python-based ML development, LLM frameworks, vector databases, and AI orchestration frameworks such as LangChain, LangGraph, and Hugging Face. Key Responsibilities: Strong Python development experience (7+ years). Hands-on experience with RAG, Vector DB, Embeddings and document chunking, Semantic search pipelines Experience with LangChain, LangGraph, and Hugging Face. Experience with Pandas, NumPy, and data preprocessing pipelines. Experience deploying ML models as REST APIs and integrating AI with enterprise systems. Required Skills & Qualifications: Mandatory in-person interview in GA or NY. Experience with enterprise level projects only - no college, educational, POC projects. Strong Python development experience (7+ years). Hands-on experience with RAG, Vector DB, Embeddings and document chunking, Semantic search pipelines. Experience with LangChain, LangGraph, and Hugging Face. Experience with Pandas, NumPy, and data preprocessing pipelines. Experience deploying ML models as REST APIs and integrating AI with enterprise systems. Preferred Qualifications: Experience with Natural Language Processing (NLP) and Deep Learning. Familiarity with Transformers and Large Language Models (LLMs). Experience with Cloud ML platforms such as Azure AI, AWS SageMaker etc. Nice to Have: Experience building AI agents or autonomous systems. Knowledge of vector databases (Pinecone, Weaviate, Milvus, FAISS). Experience with MLOps practices, Docker, and Kubernetes. Exposure to multimodal AI systems.