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Senior AI Application Development Specialist
Schneider Electric
Montréal, CAN
Full-time
Mid-Senior
Onsite
CAD 114,750 to CAD 162,000 per year
Discovered 3 weeks ago
AI application integrationLLM and machine-learning model integrationSoftware application and service developmentAPI designDistributed systemsCloud-native development
Free
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AI application integrationLLM and machine-learning model integrationSoftware application and service development
Role Overview
Join a Montréal-based Energy Intelligence team developing reliable, maintainable AI-enabled product experiences.
Build the application layer around AI models and move validated use cases from prototypes into maintained product functionality.
Work across product development, data, MLOps, architecture, and domain teams.
Key Skills for This Role
AI application integrationLLM and machine-learning model integrationSoftware application and service developmentAPI designDistributed systemsCloud-native development
Full Job Posting
Role Overview
Join a Montréal-based Energy Intelligence team developing reliable, maintainable AI-enabled product experiences.
Build the application layer around AI models and move validated use cases from prototypes into maintained product functionality.
Work across product development, data, MLOps, architecture, and domain teams.
What You Will Do
- Build production-quality AI-integrated applications and services for real product experiences.
- Integrate AI capabilities into Digital Energy Software products, developer tools, and engineering workflows.
- Develop model adapters, APIs, routing, policy enforcement, and fallback mechanisms in an AI abstraction layer.
- Create APIs, SDKs, reusable libraries, and reference applications for use across teams.
- Build script generation, validation, explanation, conversion, and review workflows.
- Implement human-in-the-loop oversight for high-impact AI decisions.
- Develop deterministic validation and testing mechanisms for probabilistic model outputs.
- Apply secure engineering to prompts, data, credentials, model responses, tool access, and telemetry.
- Contribute to testing, observability, performance optimization, and deployment.
- Help product developers turn successful prototypes into secure, maintainable capabilities.
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