Senior Data & AI Engineer

Cye is building a data-driven cybersecurity optimization SaaS platform that helps organizations

continuously improve their cyber resilience. With Cye, organizations can identify, evaluate, and remediate

the weakest links in their networks.

At Cye, we believe the best results come from combining the power of AI with deep human expertise. That’s

why we’ve built a world-class team of cybersecurity experts who augment and enhance the capabilities of

our platform.

We’re expanding our Data & AI group and looking for a passionate, experienced Senior Data & AI Engineer

to join our mission. This is a unique opportunity to work at the intersection of data engineering, LLMpowered systems, agentic workflows, and cybersecurity innovation

What You’ll Work On

• Data Infrastructure & Engineering Design, build, and scale production-grade data pipelines using Databricks, Spark, and modern cloud-native technologies. Ensure high standards of data integrity, system performance, reliability, and scalability
• Core Backend & Platform Design and contribute to scalable backend services and platform capabilities using microservices and event-driven architectures. Build reliable APIs, integrations, and asynchronous data flows that support highscale AI, data, and cybersecurity use cases
• LLM & Agentic Systems Design, prototype, and integrate LLM-powered systems, including Retrieval-Augmented Generation pipelines, agentic workflows, tool-using agents, multi-step reasoning flows, and AI-driven automation. Work with technologies such as AWS Bedrock, OpenAI, Anthropic, LangGraph, vector databases, and modern orchestration frameworks
• AI-Assisted Engineering & Developer Productivity Explore and apply advanced AI coding assistants and software-engineering agents, such as Codex and Claude Code, to improve development velocity, code quality, debugging, testing, and experimentation. Build proof-of-concepts and internal tools that help engineering and research teams work more effectively with AI-powered development workflows
• Intelligent Cybersecurity Features Collaborate with Security Researchers, Engineers, and Product teams to identify opportunities for intelligent, data-driven features that deliver actionable cybersecurity insights to customers. Transform complex cybersecurity and platform data into reliable, explainable, and useful AI-powered capabilities
  
  

• Deep understanding and hands-on experience with data lake architectures, batch processing, and real-time data processing
• Experience with tools and technologies such as Spark, Kafka, Databricks, and SQL
• Hands-on experience designing and building LLM-powered systems using providers such as OpenAI, Anthropic, AWS Bedrock, or similar platforms
• Strong practical experience with Retrieval-Augmented Generation, embeddings, vector databases, prompt engineering, evaluation techniques, and LLM orchestration frameworks such as LangGraph or OpenAI Agents SDK
• Understanding of agentic system design, including tool use, memory, planning, multi-agent collaboration, and autonomous reasoning workflows
• Experience working with advanced AI code assistants and coding agents, such as Codex, Claude Code, or similar AI-native development tools, to improve engineering productivity
• 3+ years of Python development experience in production environments. Proficiency with Git, CI/CD practices, and deploying data, automation, or AI-powered pipelines at scale
• Experience maintaining scalable, reliable AI/LLM workflows in cloud-native environments
• Strong understanding of non-functional requirements, including performance, reliability, scalability, observability, security, and cost efficiency
  
  

• Background in cybersecurity, threat intelligence, or security-focused data models
• Experience building internal developer-productivity tools, evaluation harnesses, or AI-assisted engineering workflows
• Awareness of COGS optimization and FinOps practices in SaaS data and AI systems