Senior Data Engineer

Kai is the AI company rebuilding cybersecurity for the machine-speed era. Founded by second time founders and trusted by Fortune 500 enterprises, Kai is building a future where security has no categories, no silos, and no human speed bottlenecks. The Kai Agentic AI Platform replaces fragmented, human-limited workflows with agentic AI systems that continuously contextualize, assess, reason, and execute security work at machine speed - making human defenders, superhuman.

Why Join Kai

Well-funded: With $125M raised, we have the capital, runway, and resolve to rebuild cybersecurity from first principles.

Proven: We've earned the trust of Fortune 500 and Global 1000 companies, and we're just getting started. Their confidence in Kai reflects what we've built: an AI-powered cybersecurity platform that performs at the scale and speed the enterprise demands.

Experienced founders: Our founding team consists of second-time entrepreneurs, each with over 20 years of experience in the cybersecurity industry. Their proven expertise and vision drive our ambitious goals.

World-class leadership team: Our Heads of AI, Engineering, and Product bring extensive experience from some of the world’s most influential companies, ensuring top-tier mentorship, direction, and vision.

Frontier AI Applied Research Team: Our researchers operate at the leading edge of agentic AI systems, translating breakthrough capabilities into real-world cybersecurity applications.

Generous compensation: We offer highly competitive salaries, equity options, and a supportive work environment. Your contributions will be valued and rewarded as we grow together.

THE ROLE

Kai is hiring a Sr. Data Engineer to join our data infrastructure team. This is a hands-on, high-ownership role at the core of what we do - we live on ingesting and processing data at very high speed, and this person owns the systems that make that possible.

You will design, build, and optimize the data pipelines and infrastructure that power Kai's security platform across some of the largest enterprises in the world. This is not an advisory role. You are expected to architect and implement, to identify what needs to change, and start working on it.

We are building a world-class data function. The person who joins now will have real influence over how that function evolves.

WHAT YOU'LL DO

Design and build scalable data pipelines for batch and real-time processing across Kai's agentic AI platform

Own and optimize high-volume data infrastructure handling hundreds of millions of entries with low latency and high reliability

Build and maintain data models and storage systems optimized for large-scale, high-throughput security data workloads

Identify bottlenecks in the current architecture and drive optimization - reduce processing time, improve reliability, and make the customer experience better

Lead the Terraformization of data pipelines to enable cloud-agnostic deployment across Azure, AWS, and GCP

Integrate and manage cloud data services, ensuring secure service principles, permissions, and cross-service connectivity

Collaborate closely with Backend Engineering teams on both the ingestion and consumption sides of the data pipeline

Ensure data quality, consistency, and reliability across all pipelines

Contribute to code reviews, technical documentation, and best practices

Bring a point of view - propose solutions, not just problems, and start building before you're asked

WHAT YOU'LL BRING

Required:

7+ years of experience in data engineering or data platform engineering

Must have hands-on experience handling up to 200M+ entries in materialized views in an asynchronous manner

Strong proficiency in Python and SQL - these are how our systems are written

Strong data modeling skills - you can design schemas and storage systems that hold up at scale

Experience with NoSQL databases at scale - CosmosDB, MongoDB, or equivalent

Proven experience designing and building large-scale distributed data pipelines in both batch and streaming modes

Hands-on experience with Flink, Kafka, Spark, or similar stream and batch processing frameworks

Experience with data pipeline orchestration tools - Airflow, Temporal, or equivalent

Infrastructure experience - Terraform, Kubernetes, and Docker are expected, not aspirational

Cloud platform expertise - deep hands-on experience in at least one major cloud platform (Azure, AWS, or GCP); Azure experience strongly preferred

Strong communication skills - you work cross-functionally and can explain complex systems clearly

Preferred:

DataOps experience - ability to own data infrastructure decisions independently, reducing dependency on DevOps for pipeline deployment, permissions, and service integration

Experience with data systems supporting AI/ML workloads - feature stores, ML pipelines, or dataset versioning

Experience with DeltaLake, Apache Iceberg, or similar open table formats

Startup or high-growth experience - you have operated in a fast-paced environment where things change quickly, and ownership is expected