GenAI Architect

Overview:

Primary Skills

GenAI & Agentic AI Expertise:

Development of generative & predictive AI models (NLP, Computer Vision)Agentic workflows, multi-agent systems, reinforcement learningFrameworks: LangChain/LangGraph, Crew AI, Semantic Kernel, OpenAI Agentic SDKProgramming & ML Libraries:

Python, SQLTensorFlow, PyTorch, scikit-learnPrompt Engineering:

Zero-shot, few-shot, chain-of-thought techniquesCloud & Big Data:

AWS, Azure, GCPDatabricks, PySparkSecondary Skills

API Architecture & Integration (REST, JSON, Authentication, Rate Limits)Deployment Tools: Azure DevOps, Docker, AWS ECS/EKS/FargateCI/CD: AWS CloudFormation, CodeDeployData Engineering: SQL & NoSQL (MySQL, MongoDB, Redis)Monitoring, Logging, Security & Compliance Key Responsibilities

Design & implement GenAI and predictive modelsDevelop agentic systems and autonomous AI agentsArchitect and integrate AI applications with APIsDeploy and maintain AI models in productionResearch emerging AI trends and integrate new toolsLead demos, proposals, and mentor junior team members
Skills:
Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Authentication, Big Data, Cloud Computing, Computer Vision, Continuous Deployment/Delivery, Continuous Integration, DevOps, Docker, GCP (Good Clinical Practices), JSON, Kernel Programming, Mentoring, Microsoft Windows Azure, MongoDB, MySQL, Natural Language Processing (NLP), NoSQL, Predictive Modeling, Product Demonstration, Python Programming/Scripting Language, REST (Representational State Transfer), Redis, Reinforcement Learning, SQL (Structured Query Language), Traffic Shaping, Trend Analysis

About the Company:
Purple Drive