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Job Description
- 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/deep research issues
- Implement end-to-end security and observability for production agents
- Build ETL/ELT pipelines and analytics-ready datasets on GCP
- Strong understanding of LLMs, agentic AI, multi-agent orchestration, and tool-calling concepts
- Experience building with at least one LLM platform (Gemini, OpenAI, Anthropic, etc.) and exposure to modern agent frameworks
- Familiarity with RAG architectures, agent memory systems, and prompt engineering through projects or self-directed learning
- Strong foundation in software engineering that transfers well 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, Docker
- Working knowledge of GCP services (Compute, Storage, Data, ML/AI)
- Understanding of cloud security best practices
- Experience implementing observability and monitoring
- Vector databases, Vertex AI, or knowledge graph experience
- Background in internal developer platforms or analytics infrastructure
Skills
PythonSQLLLMPrompt EngineeringRAGData EngineeringBigQueryETLGCPDockerIf a job posting appears fraudulent, asks for payment, contains misleading information, or violates our guidelines, please report it immediately. Our team will review it promptly, Jobaaj does not charge any fee from the applicants.
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