AI Architect
Why This Role Stands Out
This AI Architect role offers a fantastic opportunity to shape enterprise-scale AI and Generative AI solutions, leveraging your expertise in LLMs, RAG, and cloud platforms. If you thrive on translating complex business needs into innovative, production-ready architectures within a dynamic hybrid environment, this position is perfect for you to make a significant impact. Apply now to join a forward-thinking team and advance your career in cutting-edge AI development.
Quick Overview
Job Description
Role:- AI Architect
Location: New York, NY
Job Type: Contract
Job Description:
Experience: 12+ years overall, with 4+ years in AI/ML or Generative AI architecture
Client is seeking an experienced AI Architect to design, architect, and deliver enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will have strong hands-on experience with LLMs, RAG, Agentic AI, cloud platforms, and AI application architecture, along with the ability to translate business requirements into secure, scalable, and production-ready solutions.
Key Responsibilities
- Design end-to-end AI/ML and Generative AI architectures across application, data, and infrastructure layers.
- Architect and implement LLM-based solutions, RAG pipelines, AI agents, and multi-agent orchestration frameworks.
- Evaluate and integrate models and platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI, and other enterprise AI services.
- Design AI solutions using Python, LangChain, LangGraph, vector databases, APIs, and microservices.
- Establish AI governance, security, responsible AI practices, data privacy, and model-risk controls.
- Guide engineering teams on MLOps/LLMOps, CI/CD, model deployment, monitoring, evaluation, and optimization.
- Lead architecture reviews, technical discovery sessions, proof-of-concepts, and production implementation.
- Collaborate with business stakeholders, product teams, data scientists, developers, DevOps, and security teams.
- Define reusable AI reference architectures, design patterns, standards, and technical documentation.
- Optimize AI solutions for scalability, latency, cost, reliability, and business value.
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