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Location
Hybrid (Montreal, Canada)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Nov 9, 2026. Eeconsulting scores B on the Alion truth index.

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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.
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