GEN AI Architect NYC highly preferred Onsite Full Time

Role: GEN AI Architect

Location: NYC highly preferred Onsite

Full Time

Key Responsibilities:

• Client Advisory & Solutioning: Engage directly with senior client stakeholders (including C-suite) to understand complex business challenges, identify opportunities for GenAI and Agentic AI, and define project scope.
• Workshop Facilitation: Design, lead, and facilitate high-impact client workshops and strategy sessions focused on identifying and prioritizing Generative and Agentic AI use cases and roadmap development.
• Technical Leadership & Architecture: Design, architect, and oversee the development and deployment of scalable, robust, and cutting-edge Generative AI and sophisticated Agentic AI systems (including multi-agent workflows) for client and internal projects.
• Project & Engagement Leadership: Lead large-scale, complex Generative AI and Agentic AI projects from strategic conception through successful deployment, managing cross-functional teams (internal and client-side) and ensuring timely delivery of high-quality solutions.
• Technical Mentorship: Mentor and guide technical teams (data scientists, engineers) in best practices for advanced AI development, deployment, MLOps/LLMOps, and agentic system design.
• Stakeholder Management: Build and maintain strong relationships with key internal and external stakeholders, effectively communicating complex technical concepts and project progress.
• Quality & Best Practices: Ensure adherence to rigorous software engineering principles, Agile methodologies, and responsible AI practices throughout the solution lifecycle.
• Stay Current: Maintain deep expertise in the latest trends, research, tools, and technologies within Generative AI, Large Language Models (LLMs), and Agentic AI paradigms.

Technical Skills:

• Programming & Libraries: Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK).
• LLM Expertise: Proven experience developing applications leveraging state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude) including prompt engineering, fine-tuning, and evaluation.
• GenAI & Agentic Frameworks: Hands-on mastery of core GenAI frameworks (e.g., LangChain, LlamaIndex) and practical experience with Agentic AI frameworks and concepts (e.g., AutoGen, CrewAI, LangGraph, agent planning, tool use integration, multi-agent collaboration).
• AI Architecture: Deep understanding of AI/ML system architecture patterns, including microservices, event-driven architectures, and patterns specific to RAG (Retrieval-Augmented Generation), Graph RAG, Agentic RAG, and multi-agent systems.
• Vector Databases & Embeddings: Expertise in working with various embedding models and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS).
• Advanced AI Concepts: Strong grasp of advanced techniques such as complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for complex AI systems.
• Software Engineering: Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems.
• Cloud Platforms: Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS, Azure, Google Cloud Platform), including their AI/ML services.
• LLMOps/MLOps: Expertise in designing and implementing robust MLOps/LLMOps pipelines for automated testing, CI/CD, monitoring, and governance of complex AI models and applications.

Leadership & Communication:

• Proven ability to lead and motivate diverse, global teams
• Excellent communication skills, capable of explaining complex AI concepts to various stakeholders
• Strong project and program management skills and experience working in Agile environments

Qualifications:

• Education: Bachelor's degree in Computer Science, AI, Machine Learning, or a related quantitative field. Master's or Ph.D. strongly preferred.
• Experience: Minimum 10 years of experience in AI/ML/Data Science, with at least 5 years in significant leadership roles involving solution architecture, team management, and project delivery.
• Deployment Success: Demonstrated track record of successfully architecting and deploying large-scale AI projects, preferably including complex GenAI and/or Agentic AI applications in enterprise or client settings.
• Consulting Background: Prior experience in technology consulting or a client-facing technical specialist role within a technology provider is highly advantageous.
• Global Experience: Experience working effectively with global teams across multiple geographic locations is a plus.