Full Stack AI Engineer.
The ideal candidate should have strong expertise in both Applied AI/Generative AI and Full Stack Development. We are looking for someone who can independently design, develop, and deploy AI-powered applications, covering the complete lifecycle from AI integration and backend development to frontend implementation and cloud deployment.
Please ensure the JD covers the following technical requirements:
1. Applied AI / Generative AI (Must Have)
• Hands-on experience with LLMs, including OpenAI, Google Gemini, Anthropic, and open-source models (Hugging Face, etc.)..
• Retrieval-Augmented Generation (RAG) and vector database integration..
• AI Agent development, tool calling, and function calling..
• Multi-agent architectures and Agent-to-Agent (A2A) communication..
• Model Context Protocol (MCP) and MCP server/tool development..
• Prompt engineering and context engineering..
• Frameworks such as LangChain and related AI orchestration frameworks..
• Building AI-powered workflows, intelligent tools, and autonomous agents..
2. Frontend Development (Must Have)
• React.js and Next.js..
• JavaScript..
• Tailwind CSS..
• Vite..
• Ability to build responsive, scalable, and user-friendly interfaces..
3. Backend Development (Must Have)
• Python..
• Django and Django REST Framework (DRF)..
• FastAPI..
• Node.js..
• REST API development and third-party service integrations..
4. Database & Storage (Must Have)
• PostgreSQL..
• Qdrant..
• MySQL..
• Redis..
• Experience designing and optimizing relational and vector database solutions..
5. DevOps & Cloud (Must Have)
• AWS cloud services..
• Application deployment, hosting, and production management..
• Understanding of CI/CD, Docker, and cloud infrastructure..
6. Good to Have
• Experience with additional LLM providers and open-source AI models..
• Fine-tuning and evaluation of LLMs..
• AI observability, monitoring, and performance optimization..
• Kubernetes and infrastructure automation..
• Experience with scalable, distributed systems..
• Familiarity with emerging AI protocols, frameworks, and technologies..
Overall Expectation:
We are looking for a strong Full Stack AI Engineer who understands the AI ecosystem deeply and can translate AI capabilities into production-ready applications. The candidate should be comfortable working across AI engineering, frontend, backend, databases, and cloud infrastructure.
Important: All technologies explicitly listed under the Must Have sections should be treated as required skills, while additional relevant technologies can be included under Good to Have.
Requirements
1. Applied AI / Generative AI (Must Have)- Hands-on experience with LLMs, including OpenAI, Google Gemini, Anthropic, and open-source models (Hugging Face, etc.).
- Retrieval-Augmented Generation (RAG) and vector database integration.
- AI Agent development, tool calling, and function calling.
- Multi-agent architectures and Agent-to-Agent (A2A) communication.
- Model Context Protocol (MCP) and MCP server/tool development.
- Prompt engineering and context engineering.
- Frameworks such as LangChain and related AI orchestration frameworks.
- Building AI-powered workflows, intelligent tools, and autonomous agents.
2. Frontend Development (Must Have)- React.js and Next.js.
- JavaScript.
- Tailwind CSS.
- Vite.
- Ability to build responsive, scalable, and user-friendly interfaces.
3. Backend Development (Must Have)- Python.
- Django and Django REST Framework (DRF).
- FastAPI.
- Node.js.
- REST API development and third-party service integrations.
4. Database & Storage (Must Have)- PostgreSQL.
- Qdrant.
- MySQL.
- Redis.
- Experience designing and optimizing relational and vector database solutions.
5. DevOps & Cloud (Must Have)- AWS cloud services.
- Application deployment, hosting, and production management.
- Understanding of CI/CD, Docker, and cloud infrastructure.
6. Good to Have- Experience with additional LLM providers and open-source AI models.
- Fine-tuning and evaluation of LLMs.
- AI observability, monitoring, and performance optimization.
- Kubernetes and infrastructure automation.
- Experience with scalable, distributed systems.
- Familiarity with emerging AI protocols, frameworks, and technologies.
Overall Expectation:We are looking for a strong Full Stack AI Engineer who understands the AI ecosystem deeply and can translate AI capabilities into production-ready applications. The candidate should be comfortable working across AI engineering, frontend, backend, databases, and cloud infrastructure.
Important: All technologies explicitly listed under the Must Have sections should be treated as required skills, while additional relevant technologies can be included under Good to Have.
