Gen AI Architect

Job Description

Job Title: Gen AI Architect

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Location: Remote (USA)

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Employment Type: Full-Time

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About The Role

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We are seeking an experienced Generative AI Architect (Level 4) to lead the design, architecture, and implementation of enterprise-scale AI solutions. The ideal candidate will have deep expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), AI orchestration frameworks, and cloud-native architectures.

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Key Responsibilities

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• Design and implement enterprise-grade Generative AI and Agentic AI solutions.

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• Architect scalable AI platforms leveraging LLMs, RAG, vector databases, and multi-agent systems.

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• Lead solution design using OpenAI, Claude, Gemini, Llama, and other foundation models.

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• Develop AI architectures on AWS, Azure, or GCP with a focus on security, scalability, and performance.

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• Define best practices for prompt engineering, model evaluation, AI governance, and Responsible AI.

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• Collaborate with business stakeholders to translate business requirements into AI-driven solutions.

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• Lead technical teams through architecture reviews and solution delivery.

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• Establish MLOps/LLMOps practices for deployment, monitoring, and model lifecycle management.

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• Mentor AI engineers and development teams on GenAI technologies.

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Required Qualifications

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• Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.

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• 10+ years of overall IT experience with software engineering, cloud architecture, or AI/ML.

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• 3+ years of hands-on Generative AI architecture experience.

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• Strong expertise in Python and AI development frameworks.

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• Experience with:

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• OpenAI, Claude, Gemini, Llama

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• LangChain, LangGraph, CrewAI, AutoGen

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• RAG architectures and Vector Databases (Pinecone, Weaviate, FAISS, ChromaDB)

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• AWS Bedrock, Azure OpenAI, Google Vertex AI

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• Docker, Kubernetes, CI/CD, MLOps/LLMOps

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• Strong understanding of AI governance, security, compliance, and Responsible AI.

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• Excellent communication and client-facing skills.

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Preferred Qualifications

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• Experience designing Agentic AI and multi-agent architectures.

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• Knowledge of MCP (Model Context Protocol) and AI agent ecosystems.

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• Experience with AI observability, evaluation frameworks, and guardrails.

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• Consulting or customer-facing architecture experience.

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• Relevant cloud certifications preferred.

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