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/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

AI & Agents

- 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

Data Engineering

- Advanced SQL and BigQuery expertise

- Experience building ETL/ELT pipelines and designing semantic models

- Knowledge of contemporary cloud data warehouse architectures

Software Development

- Strong Python development skills

- Experience with APIs, distributed systems, Docker

GCP & Operations

- Working knowledge of GCP services (Compute, Storage, Data, ML/AI)

- 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

📌 Python Data Engineer (Ahmedabad)
🏢 TechBlocks
📍 Ahmedabad