Tech Lead Gen AI
Tasks
- Architect RAG pipelines ingestion chunking retrieval generation
- Champion engineering standards and best practices adoption
- Define chunking strategies and document pipeline governance
- Define network and access security patterns
- Design event driven microservices architecture on GCP
- Design source modeling strategies across Drive GCS and vector search
- Lead LLM selection decisions
- Mentor engineers with code reviews pair programming design walkthroughs
- Optimize GenAI run costs with token budgeting embedding cache model tiering
- Own Cloud Run scalability design and load testing
- Serve as technical interface with core team and AI sponsors
Perks/Benefits
- Access to training and industry experts
- Hybrid work options
- International mobility
- Learning and development
- Professional development programs
- Remote work options
Skills/Tech-stack
AI vector search | Arize AI | Cloud Monitoring | Cloud Run | Cloud platform | Embedding Cache | Google Cloud | Google Cloud Platform | IAP | LLM Evaluation | Langchain | Langsmith | Llamaindex | Model Tiering | Node.js | OpenAPI | Pinecone | Proto3 | PubSub | Python | RAG | Retrieval-Augmented Generation | Secret Manager | Service Controls | Token budgeting | TypeScript | VPC Service Controls | Vector Search | Vertex AI | Vertex AI Vector Search | Weaviate | Weights and Biases
Education
N/A
Roles
AI | AI Engineer | Architect | Engineer | Lead | Software Architect | Tech Lead
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