Agentic AI Full Stack Developer-Contract Role

Role Overview

We are seeking a highly skilled Agentic AI Full Stack Developer to design, develop, and deploy intelligent AI-powered applications. The ideal candidate will build autonomous AI agents, develop scalable full-stack solutions, integrate enterprise systems, and deliver actionable insights through dashboards and analytics.

Key Responsibilities

• Design, develop, and implement Agentic AI applications using modern AI frameworks and Large Language Models (LLMs).
• Build and maintain end-to-end full-stack web applications with intuitive and responsive user interfaces.
• Develop AI agents capable of autonomous task execution, workflow automation, and decision-making.
• Integrate AI solutions with APIs, databases, and third-party enterprise systems.
• Create dashboards, analytics, and reporting interfaces to monitor AI workflows and performance.
• Deploy and manage applications in cloud environments, ensuring reliable production releases.
• Optimize application performance, scalability, security, and maintainability.
• Collaborate with business stakeholders to translate requirements into AI-driven solutions.

Required Skills

• Strong experience in Full Stack Development (Frontend and Backend).
• Hands-on experience with Agentic AI frameworks and LLM integrations.
• Proficiency in Python programming.
• Experience in developing and consuming REST APIs and microservices.
• Strong knowledge of SQL and NoSQL databases.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of deployment processes, DevOps practices, and application monitoring.
• Experience in data visualization and dashboard development.

Preferred Skills

• Experience with LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar Agentic AI frameworks.
• Knowledge of Vector Databases and Retrieval-Augmented Generation (RAG) implementations.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Background in Data Engineering and data processing workflows.
• Familiarity with AI application security, observability, and governance best practices.