AI Lead Engineer - NLP/Python

Key Responsibilities :

- Collaborate with stakeholders to align AI initiatives with business goals.

- Lead and mentor a team of ML engineers and data scientists.

- Design, develop, and deploy enterprise-grade RAG systems that deliver accurate, context-aware responses in production environments.

- Incorporate AI agents and graph-based techniques (e.g., GraphRAG) to enable enhanced contextual data retrieval and support complex query relationships.

- Implement robust evaluation frameworks to measure and enhance RAG system effectiveness.

- Create scalable pipelines for document processing, embedding generation, and knowledge base management.

- Build monitoring systems to track performance, detect issues, and ensure RAG system reliability.

- Architect cloud-native solutions that can scale to handle enterprise document volumes and query loads.

- Explore and integrate cutting-edge techniques in Generative AI, including but not limited to model fine-tuning.

Qualifications & Skills :

- A strong foundation in Computer Science or Engineering with 5-10 years' experience in NLP, Computer Vision, Deep Learning, Machine Learning, or related field.

- Extensive experience with LLMs and related technologies (e.g., embedding models, vector databases, etc.).

- Proven expertise in developing production-grade RAG systems.

- Knowledge of graph-based RAG techniques (e.g., GraphRAG or alternatives).

- Proficiency in Python and familiarity with Generative AI frameworks such as Hugging Face, LangChain, LlamaIndex, Promptflow, AutoGen, etc.

- Hands-on experience with cloud-based AI deployments (Azure preferred).

- Experience in LLM fine-tuning and optimization (e.g., LoRA) is a plus.

- Exposure to multi-modal RAG systems and LLMOps frameworks.

- Familiarity with deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Tensorflow, etc.).