Bigdara Developer

Tech Stack & Platform Overview

The solution is built for scalable, enterprise-grade Agentic AI solutions, enabling efficient data ingestion, processing, and delivery to AI agents.

Key Components Include

Years of Experience- 3 to 5 Years

Mandatory Technical Skills

Python, Google Cloud Platform

• Core data ingestion and transformation pipelines
• Data layers supporting RAG workflows and AI agents
• LLM observability and logging data pipelines
• AgentOps-related operational data pipelines
• Integration with agent frameworks such as CrewAI, AutoGen, and LangGraph
• A modular, cloud-native architecture for rapid iteration and deployment
  
  

Responsibilities

Nice-to-Have Requirements

• Hands-on experience designing, building, and deploying data pipelines
• Experience with ETL/ELT pipelines for structured and unstructured data
• Familiarity with batch and streaming data processing
• Understanding of data quality, monitoring, and reliability practices
• Exposure to cloud-based data platforms and deployment workflows
• Basic understanding of how data pipelines support AI/LLM or RAG use cases
• Ability to collaborate with AI engineers, platform engineers, and product teams
• Willingness to learn and adapt in a fast-paced environment3.
  
  

Requirements

Mandatory Technical Skills

Python, Google Cloud Platform

• Core data ingestion and transformation pipelines
• Data layers supporting RAG workflows and AI agents
• LLM observability and logging data pipelines
• AgentOps-related operational data pipelines
• Integration with agent frameworks such as CrewAI, AutoGen, and LangGraph
• A modular, cloud-native architecture for rapid iteration and deployment
  
  

Nice to have

Nice-to-Have Requirements

• Hands-on experience designing, building, and deploying data pipelines
• Experience with ETL/ELT pipelines for structured and unstructured data
• Familiarity with batch and streaming data processing
• Understanding of data quality, monitoring, and reliability practices
• Exposure to cloud-based data platforms and deployment workflows
• Basic understanding of how data pipelines support AI/LLM or RAG use cases
• Ability to collaborate with AI engineers, platform engineers, and product teams
• Willingness to learn and adapt in a fast-paced environment3.
  
  

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office
  
  

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

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