Senior Data Engineer - AI
Role Overview
Design and implement agentic AI infrastructure on GCP, including configurable data analyst agents with multi-agent orchestration, knowledge graphs, security, and observability at scale.
Key Skills for This Role
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Role Summary
Design and implement agentic AI infrastructure on GCP, including configurable data analyst agents with multi-agent orchestration, knowledge graphs, security, and observability at scale.
Key Responsibilities
- Build multi-agent orchestration frameworks with memory and caching layers.
- Design and instrument knowledge graph architectures for agent reasoning.
- Develop conversational analytics using Gemini Enterprise, Google ADK, and MCP.
- Configure BigQuery Data Agents and address data quality and deep research issues.
- Implement end-to-end security and observability for production agents.
- Build ETL/ELT pipelines and analytics-ready datasets on GCP.
Required Qualifications
- Strong understanding of LLMs, agentic AI, multi-agent orchestration, and tool-calling concepts.
- Experience building with at least one LLM platform, such as Gemini, OpenAI, or Anthropic, and exposure to modern agent frameworks.
- Familiarity with RAG architectures, agent memory systems, and prompt engineering through projects or self-directed learning.
- Strong software engineering foundation applicable to agent systems development.
- Advanced SQL and BigQuery expertise; experience building ETL/ELT pipelines and designing semantic models.
- Knowledge of modern cloud data warehouse architectures.
- Strong Python development skills; experience with APIs, distributed systems, and Docker.
- Working knowledge of GCP compute, storage, data, and ML/AI services; understanding of cloud security best practices.
- Experience implementing observability and monitoring.
Nice to Have
- Vector databases, Vertex AI, or knowledge graph experience.
- Background in internal developer platforms or analytics infrastructure.
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