Were expanding our Data & AI group and looking for a passionate and skilled Data & AI Engineer to join our mission. This is a unique opportunity to work at the intersection of data engineering, machine learning, and cybersecurity innovation.
You'll work on:
Data Infrastructure & Engineering: Design, build, and scale production-grade data pipelines using Databricks and Spark. Ensure high levels of data integrity, system performance, and platform reliability.
AI & ML Collaboration: Collaborate with Data Scientists, Security Researchers, and Engineers to transform and deliver data for ML and GenAI model development. Build proof-of-concepts (POCs) to streamline operations such as model debugging, visualization, and experimentation.
Innovation & AI Systems: Prototype and integrate agentic workflows and LLM-powered systems (e.g., RAG, AWS Bedrock, LangGraph). Identify and develop intelligent, data-driven features that provide actionable insights to customers.
You'll work on:
Data Infrastructure & Engineering: Design, build, and scale production-grade data pipelines using Databricks and Spark. Ensure high levels of data integrity, system performance, and platform reliability.
AI & ML Collaboration: Collaborate with Data Scientists, Security Researchers, and Engineers to transform and deliver data for ML and GenAI model development. Build proof-of-concepts (POCs) to streamline operations such as model debugging, visualization, and experimentation.
Innovation & AI Systems: Prototype and integrate agentic workflows and LLM-powered systems (e.g., RAG, AWS Bedrock, LangGraph). Identify and develop intelligent, data-driven features that provide actionable insights to customers.
Requirements:
Deep understanding and hands-on experience with data lake architecture, real-time and batch processing.
Familiarity with tools like Spark, Kafka, Databricks, and SQL.
Experience designing systems powered by LLMs (e.g., OpenAI, Anthropic).
Skilled in Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, vector databases, and LLM orchestration frameworks (e.g., , LangGraph, OpenAI Agents SDK).
Understanding of multi-agent design, memory, tool-use orchestration, and autonomous reasoning agents.
3+ years of Python development experience in production environments.
Proficiency with Git, CI/CD practices, and deploying data/ML pipelines at scale.
Experience maintaining scalable, reliable ML/AI workflows in cloud-native environments.
Background in cybersecurity, threat intelligence, or exposure to security-focused data models – advantage
Strong grasp of non-functional requirements: performance, reliability, scalability, observability. And awareness of COGS optimization and FinOps practices in SaaS data systems – advantage
Deep understanding and hands-on experience with data lake architecture, real-time and batch processing.
Familiarity with tools like Spark, Kafka, Databricks, and SQL.
Experience designing systems powered by LLMs (e.g., OpenAI, Anthropic).
Skilled in Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, vector databases, and LLM orchestration frameworks (e.g., , LangGraph, OpenAI Agents SDK).
Understanding of multi-agent design, memory, tool-use orchestration, and autonomous reasoning agents.
3+ years of Python development experience in production environments.
Proficiency with Git, CI/CD practices, and deploying data/ML pipelines at scale.
Experience maintaining scalable, reliable ML/AI workflows in cloud-native environments.
Background in cybersecurity, threat intelligence, or exposure to security-focused data models – advantage
Strong grasp of non-functional requirements: performance, reliability, scalability, observability. And awareness of COGS optimization and FinOps practices in SaaS data systems – advantage
This position is open to all candidates.
