Key Responsibilities

- Design, develop, train, and deploy AI and machine learning models.

- Build AI-powered applications using Python and relevant AI frameworks.

- Work with Generative AI, LLMs, and prompt engineering.

- Develop AI solutions using NLP, computer vision, and predictive analytics.

- Integrate AI models with APIs, databases, and existing applications.

- Implement Retrieval-Augmented Generation (RAG) pipelines and vector databases.

- Prepare, clean, process, and analyze large datasets.

- Evaluate model performance, accuracy, scalability, and reliability.

- Deploy and monitor AI applications in cloud environments.

- Collaborate with software engineers, data scientists, and product teams.

- Follow best practices for AI security, responsible AI, and data privacy.

Required Technical Skills

- Programming: Python, SQL, object-oriented programming.

- Machine Learning: Scikit-learn, supervised and unsupervised learning.

- Deep Learning:



TensorFlow or PyTorch.

- Generative AI: LLMs, prompt engineering, RAG, AI agents.

- NLP: Text processing, embeddings, transformers.

- Frameworks: LangChain, LangGraph, or similar tools.

- Databases: SQL databases and vector databases such as FAISS, Pinecone, or Chroma.

- APIs: REST APIs, FastAPI, or Flask.

- Cloud & Deployment: AWS, Azure, or Google Cloud; Docker and CI/CD.

- Version Control: Git and GitHub.

Preferred Qualifications

- Experience building and deploying production-ready AI applications.

- Knowledge of model fine-tuning and evaluation.

- Familiarity with MLOps and model monitoring.

- Understanding of data structures, algorithms, and software engineering principles.

- A portfolio of AI projects on GitHub is an advantage.

📌 Artificial Intelligence Engineer (Canada)
🏢 Spait Infotech
📍 Canada