GCP GenAI/ Agentic AI Architect

Bill Sell Rate: $100/hr.Client Full Address: New JerseyRemote / WFO / Hybrid: WFOHire Type (FTE/Contract): C2HProject Duration: 8 Months, extendableExpected Start Date: 8 Jul 26Day 1 Billing Confirmation: YesNo. of client interviews for this role: 1 to 2 We have an urgent requirement of GCPGenAI/ Agentic AI Architect for our customer, Everest Insurance. Please find the required details, would request if you can share profiles quickly.Indent ID: SF_OP_205306-1-1Detailed JD: Mandatory skills - Agentic AI Frameworks Langchain, LangGraph, CrewAI, VertexAI, Autogen etc.)Good to have skills can be mentioned: Cloud Native, Microservice Architecture15+ years in software/solution architecture, proven experience as a Data Scientist or ML Engineer with exposure to agent-based AI systems.Design & Implement Agentic AI systems using agent frameworks (AutoGen, LangGraph, CrewAI, etc.) to build multi-agent and goal-oriented systems.Proficiency in Prompt Engineering, few-shot prompting, chain-of-thought reasoning, and prompt templates.Familiarity with cloud-native AI platforms from AWS, Azure, or GCP (e.g., Bedrock, Azure OpenAI, Vertex AI).Experience on AI for Engineering & working with AI Code Assist tools (e.g., Copilot, Windsurf, Cursor)Experience working with Vector databases & design & deploy RAG pipelines, MCP Servers & A2A Implement robust LLMOPs - for continuous integration, deployment, monitoring, logging, and troubleshooting mechanisms for GenAI applications.Develop and promote reusable architectural patterns, best practices, and governance frameworks for GenAI development.Lead the end-to-end architectural design of Generative AI applications, ensuring scalability, performance, security, cost-effectiveness, and maintainability.Proficiency in containerization technologies (Docker, Kubernetes) and CI/CD pipelines. Must have experience working with Microservice architecture using Spring Boot Rest APIs & know API Security, VersioningMust have experience designing CloudNative applications on any cloud such as AWS, Azure, GCP, Spring Cloud, PCFProgramming proficiency in Python (preferred), and optionally Java/Node.js for integration.Collaborate with Data Scientists, Product Owners, and Business SMEs to translate business problems into AI-powered solutions.Exceptional communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences Bill Sell Rate: $100/hr.Client Full Address: New JerseyRemote / WFO / Hybrid: WFOHire Type (FTE/Contract): C2HProject Duration: 8 Months, extendableExpected Start Date: 8 Jul 26Day 1 Billing Confirmation: YesNo. of client interviews for this role: 1 to 2 We have an urgent requirement of GCPGenAI/ Agentic AI Architect for our customer, Everest Insurance. Please find the required details, would request if you can share profiles quickly.Indent ID: SF_OP_205306-1-1Detailed JD: Mandatory skills - Agentic AI Frameworks Langchain, LangGraph, CrewAI, VertexAI, Autogen etc.)Good to have skills can be mentioned: Cloud Native, Microservice Architecture15+ years in software/solution architecture, proven experience as a Data Scientist or ML Engineer with exposure to agent-based AI systems.Design & Implement Agentic AI systems using agent frameworks (AutoGen, LangGraph, CrewAI, etc.) to build multi-agent and goal-oriented systems.Proficiency in Prompt Engineering, few-shot prompting, chain-of-thought reasoning, and prompt templates.Familiarity with cloud-native AI platforms from AWS, Azure, or GCP (e.g., Bedrock, Azure OpenAI, Vertex AI).Experience on AI for Engineering & working with AI Code Assist tools (e.g., Copilot, Windsurf, Cursor)Experience working with Vector databases & design & deploy RAG pipelines, MCP Servers & A2A Implement robust LLMOPs - for continuous integration, deployment, monitoring, logging, and troubleshooting mechanisms for GenAI applications.Develop and promote reusable architectural patterns, best practices, and governance frameworks for GenAI development.Lead the end-to-end architectural design of Generative AI applications, ensuring scalability, performance, security, cost-effectiveness, and maintainability.Proficiency in containerization technologies (Docker, Kubernetes) and CI/CD pipelines. Must have experience working with Microservice architecture using Spring Boot Rest APIs & know API Security, VersioningMust have experience designing CloudNative applications on any cloud such as AWS, Azure, GCP, Spring Cloud, PCFProgramming proficiency in Python (preferred), and optionally Java/Node.js for integration.Collaborate with Data Scientists, Product Owners, and Business SMEs to translate business problems into AI-powered solutions.Exceptional communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences

Mandatory skills - Agentic AI Frameworks Langchain, LangGraph, CrewAI, VertexAI, Autogen etc.) Good to have skills can be mentioned: Cloud Native, Microservice Architecture

• 15+ years in software/solution architecture, proven experience as a Data Scientist or ML Engineer with exposure to agent-based AI systems.
• Design & Implement Agentic AI systems using agent frameworks (AutoGen, LangGraph, CrewAI, etc.) to build multi-agent and goal-oriented systems.
• Proficiency in Prompt Engineering, few-shot prompting, chain-of-thought reasoning, and prompt templates.
• Familiarity with cloud-native AI platforms from AWS, Azure, or GCP (e.g., Bedrock, Azure OpenAI, Vertex AI).
• Experience on AI for Engineering & working with AI Code Assist tools (e.g., Copilot, Windsurf, Cursor)
• Experience working with Vector databases & design & deploy RAG pipelines, MCP Servers & A2A Implement robust LLMOPs - for continuous integration, deployment, monitoring, logging, and troubleshooting mechanisms for GenAI applications.
• Develop and promote reusable architectural patterns, best practices, and governance frameworks for GenAI development.
• Lead the end-to-end architectural design of Generative AI applications, ensuring scalability, performance, security, cost-effectiveness, and maintainability.
• Proficiency in containerization technologies (Docker, Kubernetes) and CI/CD pipelines.
• Must have experience working with Microservice architecture using Spring Boot Rest APIs & know API Security, Versioning
• Must have experience designing CloudNative applications on any cloud such as AWS, Azure, GCP, Spring Cloud, PCF
• Programming proficiency in Python (preferred), and optionally Java/Node.js for integration.
• Collaborate with Data Scientists, Product Owners, and Business SMEs to translate business problems into AI-powered solutions.
• Exceptional communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences