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. Positive 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.

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