Artificial Intelligence Engineer

- Proficiency in Python and extensive experience with AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). - Experience with state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude), including prompt engineering, fine-tuning, and evaluation. - Hands-on experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). - Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). - Strong working knowledge and practical deployment experience on major cloud platforms (AWS, Azure, GCP), including their AI/ML services. - Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems. - Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). - Proven experience in full stack development and AI/ML system implementation within enterprise environments. - Strong grasp of advanced techniques such as complex task decomposition for agents, reasoning engines, knowledge graphs, and autonomous agent design. - Excellent communication and stakeholder management skills. - Experience working on client proposals and leading technical presentations.