GenAI Lead - Location: New York - Hybrid
Title: Hands-On GenAI Lead
Experience: 15+ Years
Location: New York - Hybrid
Employment Type: Contract
Note - This is a very senior, hands-on GenAI Technical Lead / Principal Engineer role. It is not a prompt engineering or chatbot developer position—it expects someone who has architected and delivered enterprise-grade GenAI platforms.
Job Summary:-
We are looking 15+ years of experience with Hands-On GenAI Lead to design, develop, and deploy enterprise-scale Generative AI solutions. This is a senior individual contributor role requiring deep expertise in LLMs, RAG, AI agents, and cloud-native architectures. The ideal candidate will be actively involved in coding, solution architecture, technical leadership, and production deployments.
Key Responsibilities
Design and build enterprise GenAI applications using LLMs, RAG, AI agents, and orchestration frameworks.
Develop scalable AI solutions such as chatbots, copilots, document intelligence, summarization, and information extraction.
Build and deploy AI applications using Python, FastAPI, Docker, Kubernetes, and cloud platforms (AWS/Azure/Google Cloud Platform).
Implement LangChain, CrewAI, LangGraph, OpenAI, Hugging Face, and vector database solutions.
Develop CI/CD pipelines and ensure production readiness, security, observability, and AI governance.
Mentor engineering teams, review technical designs, and define best practices for enterprise AI development.
Required Skills
8+ years of software engineering experience with 4+ years in Generative AI.
Expert in Python, FastAPI, REST APIs, and cloud-native development.
Hands-on experience with OpenAI, Claude, Gemini, Hugging Face, LangChain, CrewAI, or LangGraph.
Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and multi-agent AI systems.
Experience with Docker, Kubernetes, CI/CD, Git, and AWS, Azure, or Google Cloud Platform.
Familiarity with PyTorch or TensorFlow is preferred.
Preferred Qualifications
Experience building enterprise GenAI platforms and production AI solutions.
Knowledge of AI governance, security, and responsible AI practices.
Strong communication, architecture, and technical leadership skills.
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