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Zefr

Contextual video advertising platform with privacy

Senior Software Engineer

Backend EngineeringConfirmed live in the last 24 hours
Full-timeMarina Del Rey, CA, USA$180k - $200k /yr

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science or a related field is required, along with at least 5 years of professional software engineering experience.
  • Deep hands-on experience designing, building, running, and operating microservices in Kubernetes and cloud environments such as Google Cloud Platform, Amazon Web Services, or Azure is required.
  • Proficiency using artificial intelligence for coding and research as a daily productivity tool is required, including tools such as Claude Code, GitHub Copilot, or Cursor.
  • A strong foundation in distributed systems, application programming interface design, data structures, algorithms, and software design is required.
  • Thorough testing and code review standards and practices are required.
  • The candidate must identify problems, propose solutions, and drive them to completion with minimal direction.
  • Strong collaboration skills and strong verbal and written communication skills are required.

Responsibilities

  • Own the design and implementation of microservices, and run and operate them in Kubernetes and other cloud-scalable, highly available environments.
  • Design systems for scale, reliability, and high availability, and take accountability for the operational health of owned services, including observability, alerting, and incident response.
  • Use artificial intelligence tools for coding and research as a daily part of the engineering workflow, and help the team adopt effective artificial-intelligence-assisted development practices.
  • Collaborate with product, machine learning, and infrastructure teams to translate requirements into robust technical designs.
  • Contribute to architectural decisions, design reviews, and engineering standards across the platform.
  • Mentor other engineers and communicate technical direction clearly to technical and non-technical stakeholders.

Desired Qualifications

  • Proficiency with large language models, Model Context Protocol, agent-gateway, and agentic infrastructure is a significant advantage.

About the Company

Zefr

Contextual video advertising platform with privacy

Zefr provides privacy-friendly contextual advertising, focusing on placing ads alongside video content on platforms like YouTube and Facebook without using personal data. Its Contextual Data Management Platform captures and organizes brands’ preferences to activate targeted campaigns with pre-flight targeting and impression-level transparency. The product works by analyzing contextual signals to ensure ads appear next to content aligned with a brand’s values, delivering customized video-level targeting that aims to boost metrics such as view-through rates, aided awareness, and brand favorability. Compared with competitors, Zefr emphasizes privacy compliance and transparent targeting, offering dynamic, video-focused solutions that optimize ad performance while respecting user privacy. The goal is to help brands reach the right audiences in a privacy-safe way and achieve a stronger return on investment for their video campaigns.

Company size
201-500
Company stage
Series E
Total funding
$65.1M
Headquarters
Los Angeles, CA
Founded
2009

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