AI Engineer (Generative AI / AI-ML / Microsoft Copilot)
Indexed description
Key Responsibilities
- Design, develop, and deploy AI-powered applications using modern AI frameworks.
- Build and integrate Generative AI solutions using Large Language Models (LLMs).
- Develop AI agents, copilots, chatbots, and workflow automation solutions.
- Fine-tune, prompt engineer, and optimize LLM-based applications.
- Build scalable AI/ML models and deploy them in production environments.
- Integrate AI services with enterprise applications and cloud platforms.
- Collaborate with business stakeholders to identify AI use cases and deliver innovative solutions.
- Ensure AI solutions follow security, governance, and responsible AI practices
Option 1 - Generative AI
- Hands-on experience with OpenAI GPT, Azure OpenAI, Anthropic Claude, Gemini, or Llama.
- Prompt Engineering and RAG (Retrieval-Augmented Generation).
- LangChain, LlamaIndex, Semantic Kernel, or similar AI orchestration frameworks.
- Vector Databases (Pinecone, ChromaDB, Weaviate, FAISS, Azure AI Search).
- AI Agent development and orchestration.
- Strong Python programming skills.
- Machine Learning and Deep Learning.
- TensorFlow, PyTorch, Scikit-learn.
- NLP, Computer Vision, Predictive Analytics, or Recommendation Systems.
- Model training, evaluation, deployment, and MLOps.
- Microsoft Copilot Studio.
- Copilot Agents development.
- Microsoft Power Platform.
- Microsoft Graph API.
- Azure AI Services.
- Power Automate.
- Microsoft 365 Copilot extensibility.
- Agentic AI solutions and workflow automation
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