Data & AI Engineer

A successful and profitable B2B SaaS startup in the Cybersecurity domain. The company provides security and risk management leaders with a clear, defensible view of their cyber exposure by connecting technical vulnerabilities to financial impact and real-world attack paths.

With a solid client base of large enterprises and significant funding secured, the company combines stability with cutting-edge innovation.

The offices are located in the Central District, within walking distance of the train station, offering a hybrid model with two days of work-from-home.

The Role-

• Inaugural Leadership: Build and lead the engineering infrastructure that bridges the gap between complex Cyber Data and AI.
• Production Data Architecture: Design and implement robust Data Lakes and production-grade pipelines using Databricks and Spark to handle both batch and real-time processing.
• AI & LLM Innovation: Architect advanced AI systems leveraging LLMs to transform raw security data into automated, intelligent insights.
• Agentic Systems: Develop sophisticated autonomous systems using RAG, vector databases, and Agentic system design (LangGraph, OpenAI Agents SDK).
• Engineering Excellence: Drive the deployment of large-scale AI and data automation pipelines using modern CI/CD practices and Python-based production environments.

Requirements-

• 3+ years of experience in Python development within Production environments
• Proven expertise in Data Lake architectures, Spark, Kafka, and Databricks
• Hands-on experience building LLM-based systems (OpenAI, Anthropic, AWS Bedrock)
• Strong background in RAG, Embeddings, Vector Databases, and Prompt Engineering
• Practical experience with Agentic system design and frameworks like LangGraph
• Proficiency with AI-assisted coding tools (Codex, Claude Code)
• Mastery of Git, CI/CD practices, and deploying large-scale data/AI pipelines
• Solid understanding of SQL and real-time data processing