Senior Data Engineer, AI Platform

Kai; San Jose (CA); On-site; Full time

Benefits offered by this job

Generous compensation

Equity options

Supportive work environment

Job summary

A leading AI cybersecurity company is looking for a Vector Database Engineer to design and maintain the semantic search infrastructure for its AI systems. This in-office position in North San Jose, CA, demands expertise in vector databases and programming skills. Responsibilities include managing embedding storage, implementing search pipelines, and optimizing indexing strategies. Experience with Kubernetes or cloud infrastructure is preferred, and a strong understanding of distributed systems is required. Join to contribute to cutting-edge AI solutions.

Qualifications

• Experience with vector databases such as Milvus, Pinecone, or Weaviate.
• Strong programming skills and experience with distributed systems.
• Experience working with embeddings and semantic search systems.
• Experience with Kubernetes or cloud infrastructure.

Responsibilities

• Design and manage vector database infrastructure for large-scale embedding storage.
• Implement high-performance similarity search pipelines.
• Optimize indexing strategies for large embedding dataset.
• Integrate vector search with LLM-based systems.

Skills

Vector databases (Milvus, Pinecone, Weaviate)

Programming skills

Distributed systems

Embeddings

Semantic search systems

Kubernetes

Cloud infrastructure

Job description

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 nocategories, no silos, and nohumanspeed bottlenecks.TheKaiAgentic Platformreplaces fragmented, human-limited workflows with agentic AI systems that continuously contextualize, assess, reason,and execute security work at the speed of thought-makinghuman defenders, superhuman.

Why Kai?

• $125M in Funding: We are well-funded and have the resources to innovate and scale rapidly.
• Proven Early Success with Fortune 500 Customers: We have started partnering with Fortune 500 companies, marking early success and growing trust in our innovative solutions. This highlights the immense potential and reliability of our AI-powered cybersecurity offerings.
• Experienced Leadership: Our founding team consists of second and third-time entrepreneurs, each with over 25 years of experience in the cybersecurity industry. Their proven expertise and vision drive our ambitious goals, positioning us to lead in AI-powered cybersecurity.
• 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.
• Cutting-Edge AI Solutions: Our team leverages the most advanced AI technologies, including Large Language Models (LLMs) and Generative AI.
• 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.
• Cybersecurity Knowledge Preferred but Not Required: While experience in cybersecurity is a plus, we are primarily seeking top-tier talent in microservices architecture, software development, and/or DevOps who are passionate about solving complex problems.

As a Vector Database Engineer at Kai, you will design andmaintainthe semantic search infrastructure that powers our AI systems and RAG platforms.

You Will:

• Design and manage vector database infrastructure for large-scale embedding storage.
• Implement high-performance similarity search pipelines.
• Optimize indexing strategies for large embedding dataset.
• Integrate vector search with LLM-based systems.

You Have:

• Experience with vector databases such as Milvus, Pinecone, or Weaviate.
• Strong programming skills and experience with distributed systems.
• Experience working with embeddings and semantic search systems.
• Experience with Kubernetes or cloud infrastructure.

Work Location

This is a 5-days a week in-office role based in North San Jose, CA.