About the Role:

Role : Senior AI Engineer Location : Toronto and Haliflax(2x week onsite) Duration : Long Term Contract

Position Summary We are seeking an experienced Senior AI Engineer to lead the design, development, and deployment of enterprise-grade Artificial Intelligence (AI) and Machine Learning (ML) solutions. The successful candidate will have extensive experience in developing scalable AI applications, implementing Generative AI technologies, and delivering production-ready machine learning systems. This role requires close collaboration with cross-functional teams to transform business requirements into innovative AI-driven solutions while ensuring high standards of performance, security, and reliability. Key Responsibilities Design, develop, deploy, and maintain scalable AI and machine learning solutions in production environments. Build enterprise-grade Generative AI applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures. Develop and optimize AI agents, prompt engineering strategies, and orchestration workflows. Fine-tune, evaluate, and monitor machine learning and foundation models for performance, accuracy, and reliability. Design and implement scalable data pipelines, feature engineering processes, and model deployment workflows. Collaborate with Product Managers, Data Scientists, Software Engineers, and business stakeholders to define AI solution strategies. Integrate AI solutions with enterprise applications, APIs, and cloud-native services. Implement MLOps best practices, including CI/CD pipelines, model versioning, monitoring, and governance. Ensure AI solutions comply with security, privacy, and Responsible AI principles. Provide technical leadership, mentor junior engineers, and contribute to architectural decisions and engineering best practices. Evaluate emerging AI technologies and recommend improvements to existing platforms and solutions. Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related discipline. Minimum 7 years of software engineering experience, including at least 4 years developing AI/ML solutions in production environments. Strong proficiency in Python and experience with software engineering best practices. Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn. Experience developing applications using Large Language Models (LLMs) and Generative AI technologies. Experience implementing Retrieval-Augmented Generation (RAG), vector search, embeddings, and AI agent frameworks. Strong understanding of prompt engineering, model evaluation, and LLM optimization techniques. Experience developing RESTful APIs and microservices. Experience with Docker, Kubernetes, and containerized deployments. Strong knowledge of SQL, NoSQL databases, and vector databases. Experience implementing CI/CD pipelines and MLOps practices. Excellent analytical, communication, and problem-solving skills. Preferred Qualifications Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform. Experience with MLflow, Kubeflow, Azure Machine Learning, Amazon SageMaker, or Google Vertex AI. Experience with distributed computing technologies such as Spark or Ray. Knowledge of Responsible AI, model governance, AI security, and regulatory compliance. Experience mentoring technical teams and leading complex AI initiatives. Professional cloud or AI certifications are considered an asset. Technical Skills Programming Languages Python SQL Java or C# (preferred) Artificial Intelligence & Machine Learning PyTorch TensorFlow Scikit-learn Hugging Face Transformers LangChain LlamaIndex OpenAI APIs or equivalent LLM platforms Vector databases (Pinecone, Weaviate, Milvus, Chroma, FAISS) Cloud & DevOps AWS, Microsoft Azure, or Google Cloud Platform Docker Kubernetes Git CI/CD pipelines Terraform (preferred) Data Technologies PostgreSQL MongoDB Redis Snowflake Vector databases Competencies Strong technical leadership and mentoring capabilities Excellent communication and stakeholder engagement skills Strategic thinking and solution-oriented mindset Ability to manage multiple priorities in a fast-paced environment Strong commitment to quality, innovation, and continuous improvement