Experience:

• 2-3 years of hands-on experience in AI / ML or Generative AI engineering
• Proven experience building LLM-based applications, AI agents, or RAG systems
• Experience taking AI solutions from prototype to production

Qualification:

• Bachelor's or Master's degree in Computer Science, AI, ML, or a related field

Role Focus:

• Design, build, and deploy AI agents and multi-agent workflows
• Develop AI automation pipelines using LLMs, tools, and APIs
• Build and optimize RAG (Retrieval-Augmented Generation) systems
• Integrate and manage LLM APIs
• Develop production-ready backend APIs using Python
• Monitor and optimize AI systems for quality, latency, and cost
• Mentor junior engineers and ensure clean, scalable implementations

Nice to have:

• Experience with LlamaIndex, LangGraph, AutoGen, and Semantic Kernel
• Fine-tuning or serving open-source LLMs (LLaMA, Mistral, Falcon)
• Knowledge of PyTorch or TensorFlow
• Experience with MLOps / LLMOps (CI/CD, deployment, monitoring)
• Cloud platforms: Azure / AWS / GCP
• Experience with AI copilots or enterprise chatbots
• Cost optimization for LLM-based systems
• Familiarity with low-code automation tools (n8n, Make)

More skills:

Large Language Models (LLMs), RAG systems, LLM APIs (OpenAI, Azure OpenAI, open-source models)

Other:

• Join a distributed team that values clear communication, continuous learning, and ownership
• Build software that matters from scalable cloud platforms to AI-powered tools that solve real business problems