AIML Architect

Careernet; Chennai; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Careernet is seeking an experienced AI architect to design and implement MCP-based, agentic AI solutions in Chennai, India. You will architect autonomous systems, lead MCP deployments, and develop full-stack AI apps using React/Next.js/Node.js/TypeScript while evaluating Anthropic and OpenAI models.

You will also establish governance, mentor teams, and drive best practices in prompt engineering, RAG, and performance optimization to deliver scalable AI capabilities within enterprise contexts.

Responsibilities

• Design and architect AI-powered solutions using MCP and agentic AI frameworks. Define AI integration patterns that align with Staples technical strategy and business objectives.
• Architect agentic AI systems capable of autonomously reasoning, planning, and executing complex workflows. Implement multi-step reasoning, function calling, and tool orchestration to enable intelligent automation.
• Lead MCP implementations to enable seamless integration between AI models and enterprise data sources, APIs, and internal systems. Design and optimize MCP servers and clients for performance, scalability, and reliability.
• Develop full-stack AI applications using React, Next.js, Node.js, and TypeScript that leverage advanced AI capabilities. Build responsive user interfaces that effectively interact with AI backends and agentic systems.
• Evaluate and integrate cutting-edge LLMs and AI frameworks, including models from Anthropic and OpenAI (e.g., Claude and GPT). Stay current with the rapidly evolving AI landscape and recommend technologies for adoption.
• Implement prompt engineering best practices, fine-tuning strategies, and Retrieval-Augmented Generation (RAG) architectures. Design AI solutions that optimize accuracy, cost, latency, and overall user experience.
• Establish governance and security frameworks for AI systems, including bias mitigation, explainability, compliance, and responsible AI practices. Develop monitoring mechanisms to track AI model performance and behavior.
• Mentor and guide engineering teams on AI integration, agentic architecture patterns, and MCP implementations. Promote knowledge sharing through documentation, workshops, and cross-team collaboration to accelerate AI adoption.

Job description

Key Responsibilities

1. Design and architect AI-powered solutions using Model Context Protocol (MCP) and agentic AI frameworks. Define AI integration patterns that align with Staples technical strategy and business objectives.
2. Architect agentic AI systems capable of autonomously reasoning, planning, and executing complex workflows. Implement multi-step reasoning, function calling, and tool orchestration to enable intelligent automation.
3. Lead Model Context Protocol (MCP) implementations to enable seamless integration between AI models and enterprise data sources, APIs, and internal systems. Design and optimize MCP servers and clients for performance, scalability, and reliability.
4. Develop full-stack AI applications using React, Next.js, Node.js, and TypeScript that leverage advanced AI capabilities. Build responsive user interfaces that effectively interact with AI backends and agentic systems.
5. Evaluate and integrate cutting-edge LLMs and AI frameworks, including models from Anthropic and OpenAI (e.g., Claude and GPT). Stay current with the rapidly evolving AI landscape and recommend technologies for adoption.
6. Implement prompt engineering best practices, fine-tuning strategies, and Retrieval-Augmented Generation (RAG) architectures. Design AI solutions that optimize accuracy, cost, latency, and overall user experience.
7. Establish governance and security frameworks for AI systems, including bias mitigation, explainability, compliance, and responsible AI practices. Develop monitoring mechanisms to track AI model performance and behavior.
8. Mentor and guide engineering teams on AI integration, agentic architecture patterns, and MCP implementations. Promote knowledge sharing through documentation, workshops, and cross-team collaboration to accelerate AI adoption.