DevOps Engineer - Networking

**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.

**Why This Role Matters**
This role focuses on automating workflows, improving platform reliability, and supporting data engineering teams with efficient development and deployment practices. In a world where digital experiences shape trust and adoption, DataOps increases development productivity which directly drives product success and customer confidence.
What You’ll Do

• Design, deploy, and operate scalable data platforms and pipelines, primarily on Azure (Databricks, ADF, ADLS)
• Build, manage, and optimize Apache Spark clusters and workloads for batch and streaming data processing across Azure and AWS environments.
• Implement CI/CD pipelines for data engineering code, Spark jobs, and pipeline configurations using Azure DevOps/GitHub Actions
• Automate infrastructure using Infrastructure as Code (Terraform) and manage containerized workloads with Docker and Kubernetes
• Monitor data pipelines and platforms to ensure data reliability, quality, observability, and cost optimization across Azure and AWS data platforms.
• Enforce security, governance, and best practices, collaborating closely with data engineers and platform teams in Azure-first, multi-cloud environments.

What We’re Looking For

• 6+ years of professional experience in data engineering, Data DevOps, or Data platform engineering roles
• Proven experience supporting production-grade data platforms in enterprise environments
• Proven ability to design, build, deploy, and maintain scalable data pipelines (ETL/ELT)
• Deep understanding of Apache Spark for batch and streaming workloads
• Experience creating, configuring, and managing Spark clusters, including performance tuning and cost optimization
• Practical experience with at least one major cloud provider: AWS, Azure, or GCP.
• Strong experience using Terraform for infrastructure automation.
• Proven ability to diagnose and resolve system and infrastructure issues.
• Bonus Skill: Experience deploying and managing Spark workloads on Azure Databricks or Azure Synapse

**Work Location – San Jose, CA (5 days in the office)**