Fullstack Data Engineer - Applied & Agentic AI Systems

Overview

Fullstack AI Data Engineer for agentic, LLM-based solutions in an autonomous development squad, covering the full lifecycle from prototyping to production operations.

What you'll do

• Collaborate with AI engineers, data scientists, product owners, and developers to integrate LLMs into scalable end-user applications.
• Design and implement scalable, high-performance data pipelines for AI/GenAI applications, including ingestion, transformation, storage, and retrieval.
• Build vector database solutions to enable similarity search and RAG for generative AI.
• Work with graph databases to support GraphRAG and multi-hop logical reasoning for agentic workflows.
• Develop cloud-based data solutions using AWS and/or Azure services.
• Create ETL/ELT pipelines for real-time and batch data processing.
• Set up monitoring, alerting, and logging for data pipelines to ensure high availability and reliability.

What you'll need

• 7+ years of data engineering experience, preferably supporting AI/ML applications.
• Production-grade Python development and highly optimized, complex SQL.
• Ability to design scalable, fault-tolerant ETL/ELT pipelines and Lakehouse architectures (e.g., Snowflake).
• Hands-on orchestration experience with tools like Airflow.
• Develop RAG and AI systems using vector databases and/or LLM fine-tuning, plus data preparation.
• Document processing skills to extract, transform, and load from formats like PDF, DOCX, CSV, and JSON.
• Experience with Git, CI/CD, Docker/Kubernetes, and Infrastructure as Code (Terraform/CloudFormation).

Details

• Location: Hyderabad, India.
• Working hours structured for overlap with Central European Time.