🛠 Tech Stack

💼 About This Role

You'll architect the "paved road" for AI initiatives, transitioning prototypes into robust, observable systems. You'll be the bridge between AI research and enterprise-grade reliability, enabling faster and safer feature delivery. This role focuses on building scalable data infrastructure for agentic AI systems, LLM-based agents, and multi-agent workflows.

🎯 What You'll Do

• Architect and build scalable data infrastructure for LLM-based agents.
• Design batch and real-time data pipelines for embeddings and RAG systems.
• Develop vector database solutions for low-latency retrieval.
• Build data frameworks for training, evaluation, and benchmarking.
• Implement data governance, quality controls, and security compliance.

📋 Requirements

• 5+ years building large-scale data platforms as a Data Engineer.
• Strong programming expertise in Python and SQL.
• Experience with batch and real-time data pipelines (e.g., Kafka or Kinesis).
• Experience with cloud platforms (AWS, Azure, or GCP) and tools like Snowflake.

✨ Nice to Have

• Experience with agentic AI systems, multi-agent architectures, or tool-using AI agents.
• Familiarity with agent memory models, conversation histories, and reasoning trace storage.
• Experience with synthetic data generation and simulation frameworks.

🎁 Benefits & Perks

• 🏖️ Flexible remote work
• 💰 Competitive base compensation
• 🏥 Comprehensive benefits package
• 📈 Growth opportunities

📨 Hiring Process

Estimated timeline: 2-3 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min

[email protected]