AI Engineer (Data)
Tasks
- Architect and optimize data structures and data warehouse access patterns
- Build knowledge retrieval and search systems using large language models
- Define success metrics and improve AI products based on adoption accuracy efficiency and impact
- Design develop and maintain AI agents for natural language data interaction
- Develop internal AI tools reusable agent components workflow automations
- Establish evaluation monitoring and observability frameworks for AI systems
- Implement retrieval context management tool calling and multi step reasoning workflows
- Prototype evaluate and productionize AI driven solutions with analysts and engineers
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | Airflow | Automated Quality | Automated Quality Assessment | BigQuery | Context Management | DBT | Data Architecture | Data Modeling | Data Pipelines | Data Warehouse | Evaluation Frameworks | Google ADK | Haystack | Knowledge Retrieval | LLM orchestration | LLM-as-a-Judge | Langchain | Language Models | Large Language Models | Llamaindex | Monitoring | Multi-step reasoning | Observability | PII protection | Prompt injection | Prompt injection mitigation | Prompting | Quality Assessment | RAG | Ragas | Retrieval-Augmented Generation | Risk Management | SQL | Security Risk | Security Risk Management | Tableau | Tool-Calling
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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