Senior Data/AI Engineer
Tasks
- Architect and build production backend services and APIs
- Deploy and manage AI applications in production
- Evaluate prompt strategies and model performance
- Implement LLMOps best practices
- Integrate LLMs with knowledge repositories and external data sources
- Mentor engineers through code reviews and design discussions
- Monitor AI systems and maintain reliability
- Optimize retrieval-augmented generation pipelines
- Own end to end AI application lifecycle
- Translate user needs into technical AI requirements
Perks/Benefits
- Company RRSP match
- Comprehensive benefits plan
- Development opportunities via LinkedIn Learning
- Paid time off
Skills/Tech-stack
AI Observability | Agent systems | Alerting | Anthropic | Apache Spark | ArgoCD | Asyncio | Azure Kubernetes | Azure Kubernetes Service | CI/CD | Chain-of-Thought | Chunking | Databricks | Docker | Elasticsearch | FastAPI | Flask | Gemini API | Helm | Kubernetes | Kubernetes Service | LLM Evaluation | LLMOps | Langchain | Language Models | Large Language Models | Llamaindex | MLflow | Microservices | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | OpenAI API | Pinecone | Prompt engineering | Python | REST API | React | Reranking | Retrieval-Augmented Generation | Testing | Tool-Calling | Vector Databases | Zero-downtime | Zero-downtime deployment
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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