AI Engineer

📋 Description

• Architect and build scalable backend services and APIs for Generative AI.
• Own end-to-end AI app lifecycle: design, CI/CD, monitoring in Databricks/AKS.
• Optimize RAG pipelines: tune retrieval, chunk sizes, re-rankers, prompts.
• Integrate LLMs with knowledge bases, external APIs, and real-time data streams.
• Champion LLMOps and engineering best practices: automated evals, observability.
• Evaluate and implement AI strategies: prompt engineering for safety.

🎯 Requirements

• 6+ years backend engineering with Generative AI; or 4+ years with Master's.
• Python, FastAPI/Flask, asynchronous programming; REST APIs.
• REST, microservices; CI/CD (ArgoCD); observability and uptime.
• Azure cloud; Docker; Kubernetes; Helm.
• 2+ years with LLMs; RAG and vector DBs (Pinecone/Elasticsearch).
• LangChain or LlamaIndex for LLM apps; leadership experience preferred.

🎁 Benefits

• Paid Time Off
• Comprehensive benefits plan
• Company RRSP Match
• Development opportunities via LinkedIn Learning