Senior AI Engineer
Tasks
- Analyze failure modes
- Architect AI layer
- Automate internal workflow tools
- Benchmark model value
- Build LLM function calling
- Build agentic workflows
- Collaborate on technical specifications
- Design dynamic routing
- Design testing strategies
- Develop RAG architectures
- Ensure AI subsystem scalability
- Ensure production reliability
- Execute experimentation for model evaluation
- Implement multi-agent systems
- Integrate vector stores
- Iterate prompts and model configurations
- Maintain technical documentation
- Measure output quality
- Monitor output quality
- Orchestrate autonomous agents
- Test LLM responses
- Troubleshoot complex subsystem issues
Perks/Benefits
- Birthday off
- Generous vacation package
- Health days
- Health spending account
- Hybrid work
- Personal day
- Personal development budget
- RRSP Group Savings Plan
- Stock options
- Volunteering days
- Work from anywhere
Skills/Tech-stack
Agent Orchestration | Agent systems | Artificial Intelligence | Autonomous Agents | Dynamic routing | Function Calling | LLM Evaluation | LLM monitoring | Language Models | Large Language Models | Machine Learning | Multi-Agent | Multi-Agent Systems | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SQL | System Reliability | Testing | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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