Senior AI/GenAI Engineeri in GA/NY; Hybrid
Listed on 2026-07-01
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
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 Lang Chain, Lang Graph, 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 Lang Chain, Lang Graph, and Hugging Face.
- Experience with Pandas, Num Py, 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 Lang Chain, Lang Graph, and Hugging Face.
- Experience with Pandas, Num Py, 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 Sage Maker 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.
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