Related skills
python kubernetes databricks flask fastapi📋 Description
- Architect and build scalable backend services for Generative AI, incl. RAG pipelines.
- Own end-to-end AI app lifecycle: design, deployment, monitoring, on Databricks/AKS.
- Improve RAG pipelines with retrieval tuning, chunking, and prompt engineering.
- Integrate LLMs with knowledge bases, external APIs, and real-time data.
- Lead LLMOps and engineering best practices: observability and automated evaluation.
- Mentor engineers and influence the AI product roadmap.
🎯 Requirements
- 6+ yrs backend and Generative AI; degree required.
- Strong Python, FastAPI/Flask, async; RESTful APIs and microservices.
- Cloud infra: Azure preferred; Docker, Kubernetes, Helm.
- 2+ yrs production AI apps with LLMs; RAG, vector DBs (Pinecone/Elasticsearch), multi-agent tools.
- AI system design/evaluation: frameworks like LLM Judges or MLflow; monitoring.
- Large-scale data processing: Databricks, Apache Spark.
- LangChain or LlamaIndex familiarity.
- Leadership and mentorship: lead engineers and projects.
🎁 Benefits
- Paid Time Off
- Comprehensive benefits plan
- Company RRSP Match
- Development opportunities through LinkedIn Learning
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