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 solid 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.

📌 Full Stack AI Engineer (Chandigarh)
🏢 CrossML Private
📍 Chandigarh