Senior AI Engineer

 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 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 

• 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.