Senior AI Engineer

Company Description Ayata.AI | Senior AI Engineer Montreal, QC | Hybrid, 2–3 days per week onsite | Ayata.AI About Ayata develops AI-powered software for complex industry problems. We are looking for a Senior AI Engineer to design and build solutions that use AI to understand, transform, migrate, and improve software systems and codebases. This is a hands-on role combining applied AI, software engineering, and cloud delivery. Job Description Job Responsibilities and Duties Build AI-assisted solutions for code analysis, system transformation, refactoring, and migration. Analyze application architecture, source code, dependencies, data, metadata, and logs. Design and integrate generative AI, NLP, retrieval, and other machine learning capabilities into migration workflows. Develop reliable pipelines to generate, test, validate, and deploy transformed code and software components. Create evaluation methods for functional correctness, regression, performance, security, and maintainability. Build cloud-based AI services, APIs, data pipelines, and automation for production use. Apply sound software engineering practices, including clean code, testing, documentation, versioning, and traceability. Provide technical guidance and mentor engineers while remaining directly involved in design and development. Qualifications Qualifications 5–10 years of relevant experience in software engineering, AI, machine learning, or system modernization. MSc or PhD in Computer Science, Machine Learning, Software Engineering, or a related field. Strong Python programming skills and experience delivering production software. Experience with generative AI, NLP, embeddings, retrieval-augmented generation, or related AI methods. Experience with PyTorch, TensorFlow, or equivalent machine learning frameworks. Strong understanding of software architecture, APIs, dependency management, testing, and system integration. Experience working with structured and unstructured data, SQL, and data transformation pipelines. Experience with cloud platforms such as Azure, AWS, or Google Cloud, and container technologies such as Docker. Ability to explain technical decisions clearly and work effectively in evolving problem spaces. Additional Qualifications Experience with code intelligence, static analysis, parsers, abstract syntax trees, compilers, or dependency graphs. Experience migrating or modernizing applications across languages, frameworks, databases, or cloud environments. Experience with MLOps tools, model evaluation, experiment tracking, monitoring, and scalable inference. Experience building developer tools or AI-assisted software engineering platforms. Experience with enterprise systems in Energy, Insurance, Healthcare, or another regulated industry.