Senior AI Data Engineer

We are seeking an experienced Senior Data Engineer to lead the development and optimization of data infrastructure supporting our Agentic AI initiatives. You will collaborate with ML engineers, AI scientists, and product managers to architect, implement, and maintain robust data pipelines powering autonomous AI agents.

Requirements

• Design, develop, and maintain scalable data pipelines and ETL processes supporting AI research and development.
• Design and maintain scalable data models (e.g., star schemas, feature-ready datasets, semantic layers) for analytics, ML training, and agent workflows.
• Collaborate with AI scientists and engineers to gather data requirements and ensure availability and quality.
• Implement data governance and security measures to protect sensitive information.
• Establish observability, lineage tracking, and monitoring frameworks to detect anomalies, freshness issues, and operational failures.
• Implement data partitioning, indexing, and storage optimization techniques for large-scale AI datasets.
• Monitor and troubleshoot data pipeline issues to ensure continuity and reliability.
• Stay current with emerging data engineering and AI technologies.
• Drive data platform reliability, scalability, and cost optimization across cloud-based infrastructure.
• Design and implement scalable, resilient data architectures for AI agent training, fine-tuning, and inference workflows.
• Build streaming and event-driven pipelines enabling real-time agent feedback, telemetry, and adaptive learning.
• Develop and maintain high-performance pipelines using modern orchestration frameworks to support real-time agent interactions.
• Create specialized storage and retrieval systems for vector embeddings, knowledge graphs, and symbolic reasoning components.
• Implement automated data validation, schema testing, and quality checks ensuring reliable AI training datasets.
• Implement comprehensive monitoring and governance frameworks ensuring high-quality training data and compliance with privacy regulations.
• Continuously optimize system performance with a focus on reducing latency for agent decision-making.