Senior Data Engineer Agentic AI & Cloud Platforms Bangalore
Summary
Senior Data Engineer who designs, builds, and operates production-grade batch and streaming data pipelines on Google Cloud Platform, while integrating agentic AI and LLM frameworks (LangChain, LlamaIndex) such as tool calling, memory, and RAG into production data systems. Core stack: Python, Java, Spring Boot, dbt, and Spark on GCP.
Directly tied to vibe coding — integrates agentic AI and LLM frameworks (LangChain/LlamaIndex) for autonomous agents and LLM-driven pipelines.
About the Role
Senior Data Engineer focused on building production-grade batch and streaming data pipelines on Google Cloud Platform while integrating agentic AI and LLM frameworks to enable autonomous workflows and LLM-based reasoning in production systems.
Job Description
Role
Senior Data Engineer working on Agentic AI & Cloud Platforms in Bangalore. The role centers on designing, building, and operating production-grade batch and streaming data pipelines and integrating agentic AI capabilities and LLM frameworks into data platforms on Google Cloud Platform (GCP).
Key Responsibilities
- Design and implement production-grade batch and streaming data pipelines.
- Build and operate distributed data systems and analytical platforms.
- Integrate LLM frameworks and agentic AI concepts (tool calling, memory, autonomous agents) into production systems.
- Collaborate with platform and engineering teams to deploy and scale data infrastructure on GCP.
Requirements
- 8+ years of experience in data engineering or platform engineering roles.
- Strong proficiency in Python and Java.
- Experience with Spring Boot, dbT, and Apache Spark.
- Hands-on experience with Google Cloud Platform (GCP).
- Proven experience building production-grade batch and streaming data pipelines.
- Strong understanding of distributed data systems and analytical platforms.
- Solid understanding of agentic AI principles: autonomous agents/workflows, tool calling, memory, and LLM-based reasoning in production.
- Experience with LLM frameworks (examples listed: LangChain, LlamaIndex, or custom agent frameworks).
- Familiarity with prompt engineering, retrieval-augmented generation (RAG), and embeddings.
Technologies
Explicitly mentioned: Python, Java, Spring Boot, dbT, Spark, Google Cloud Platform (GCP), LangChain, LlamaIndex.
Python Java Spring Boot dbT Spark Google Cloud Platform (GCP) LangChain LlamaIndex
Skills
Data Engineering Platform Engineering Distributed Systems Streaming Data Batch Processing Production Systems Analytical Platforms Agentic AI LLM Deployment Prompt Engineering Retrieval-Augmented Generation (RAG) Embeddings Systems Design