AI Engineer
Tasks
- Architect and build production AI systems
- Deploy and operate systems with CI CD
- Design and maintain evaluation frameworks
- Develop low latency backend services and APIs
- Engineer multi agent AI systems with tool calls
- Evaluate and tune prompts and model interactions
- Implement LLMOps and monitoring
- Influence AI product roadmap
- Integrate LLMs with knowledge repositories and APIs
- Lead code reviews and mentorship
- Optimize RAG pipelines
- Own end to end AI application lifecycle
Perks/Benefits
- Company RRSP match
- Comprehensive benefits plan
- Development opportunities through LinkedIn Learning
- Paid time off
Skills/Tech-stack
AI Observability | Agent systems | Alerting | Anthropic | Apache Spark | ArgoCD | Asynchronous programming | Asyncio | Azure | CI/CD | Chain-of-Thought | Chunking | Databricks | Docker | Elasticsearch | FastAPI | Flask | Google Gemini | Helm | Kubernetes | LLM Judges | LLMOps | Langchain | Language Models | Large Language Models | Llamaindex | MLflow | Microservices | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | OpenAI | Pinecone | Prompt engineering | Python | RAG | RESTful APIs | React | Retrieval optimization | Retrieval-Augmented Generation | Testing | Vector Databases | Zero-downtime | Zero-downtime deployments
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | AI/ML Engineer | Engineer | ML Engineer
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