Full Stack Developer (Multi-Agentic AI)

Job Description – Full Stack Developer (Multi-Agentic AI)

Day to Day Job Duties:

• Design, develop, and maintain enterprise-grade full-stack applications using React, TypeScript, Python, and FastAPI.
• Build responsive and accessible user interfaces that enable business users to interact with AI agents, workflows, enterprise data, and business systems.
• Develop conversational and chat-based AI experiences, including agent responses, recommendations, workflow tracking, approvals, and human-in-the-loop interactions.
• Design and implement secure, scalable REST APIs and backend services using FastAPI, Python, and Pydantic.
• Build asynchronous services, business logic, authentication and authorization controls, data validation, logging, monitoring, and API documentation.
• Integrate applications with LLMs, Agentic AI platforms, AI orchestration services, and multi-agent ecosystems.
• Develop APIs and services supporting tool/function calling, agent-to-agent interactions, session management, agent memory, workflow orchestration, and long-running AI processes.
• Implement RAG (Retrieval-Augmented Generation), vector search, streaming AI responses, and enterprise AI integrations.
• Build secure integrations with enterprise platforms including SAP, Microsoft 365, SharePoint, databases, document repositories, API gateways, and business applications.
• Implement automated testing, CI/CD pipelines, containerized deployments, observability, and secure software engineering best practices.
• Collaborate with AI Engineers, Solution Architects, Cloud Engineers, Security Engineers, Product Owners, and Technical Delivery Managers to deliver production-ready AI solutions.

Basic Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• Strong hands-on experience developing full-stack applications using React, TypeScript, HTML5, CSS, Python, and FastAPI.
• Experience designing and developing REST APIs, asynchronous services, API integrations, and enterprise application architectures.
• Strong knowledge of Pydantic, authentication and authorization mechanisms, automated testing, CI/CD, Git, Docker, and secure development practices.
• Experience building scalable, resilient, and production-grade cloud-native applications.
• Ability to work across both frontend and backend technologies within a full-stack development model.
• Strong analytical, problem-solving, and stakeholder communication skills.

Preferred Qualifications:

• Experience building Generative AI, Agentic AI, and Multi-Agent AI solutions.
• Knowledge of LLMs, RAG, AI orchestration, tool/function calling, structured outputs, prompt engineering, agent memory, state management, and vector databases.
• Experience with LangChain, LangGraph, Azure OpenAI, Azure AI Services, Amazon Bedrock, Model Context Protocol (MCP), and Agent-to-Agent (A2A) integrations.
• Hands-on experience with streaming AI responses, multi-agent workflows, and enterprise AI solution delivery.
• Exposure to Azure cloud services, modern DevOps practices, and consulting-led development environments.
• Experience integrating AI solutions with enterprise platforms such as SAP, Microsoft 365, SharePoint, and other line-of-business applications.