About the role
We are looking for a hands-on Senior Full-stack AI Engineer who can independently design, develop, test, and deploy end-to-end agentic AI applications using React.js and Python. You will be responsible for taking a business requirement, breaking it into modules, deciding the application architecture, designing data structures and APIs, integrating AI components, and delivering a fully functional, production-ready solution. Need someone who can think independently, make technical decisions, integrate services, and take complete ownership of the application lifecycle as an individual contributor.
Responsibilities:
- End-to-End Development: Build complete AI applications using React.js for the frontend and Python for the backend.
- Solution Design: Understand business requirements, divide work into modules, and define application architecture, data structures, and API requirements.
- Agentic AI Development: Integrate LLMs, RAG pipelines, AI agents, tool calling, and frameworks such as LangChain and LangGraph.
- Service Integration: Integrate third-party APIs, databases, AI models, MCP servers, and other required services and protocols.
- Database Design: Design and manage relational databases and vector databases based on application requirements.
- Deployment and Infrastructure: Handle end-to-end deployment, CI/CD pipelines, Docker, cloud infrastructure, and production releases.
- Testing and Quality: Perform end-to-end testing, including unit, integration, functional, and smoke testing, to ensure application reliability.
- Performance and Security: Monitor application performance, troubleshoot issues, and follow secure coding and deployment practices.
- Ownership and Communication: Work independently, communicate effectively with stakeholders, provide regular updates, and support off-hours activities when required by business needs.
Requirements:
- Strong hands-on experience with React.js, JavaScript/TypeScript, and modern frontend development.
- Strong Python programming skills with experience in Fast API, Django, or similar backend frameworks.
- Practical experience building and deploying end-to-end AI applications.
- Good understanding of LLMs, RAG, vector databases, prompt engineering, and AI agent workflows.
- Experience with frameworks such as LangChain or LangGraph.
- Understanding of MCP, tool calling, function calling, and API integrations.
- Experience with SQL/NoSQL databases, REST APIs, and data modeling.
- Experience with Docker, CI/CD, cloud platforms, and production deployments.
- Hands-on experience with automated testing frameworks such as PyTest and Jest.