Agentic Engineer at Zefr

London, England, United Kingdom

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Advertising, AI, TechnologyIndustries

Requirements

4+ years’ full-stack engineering experience (with Python, Java, Go, or similar)
Hands-on cloud experience (AWS or GCP) with services for compute, data, and AI/ML
Proven skills in data engineering (ETL pipelines, APIs, SQL/NoSQL, data warehouses like BigQuery/Redshift)
Experience with AI agents, LLMs and orchestration frameworks (LangChain, AutoGen, LlamaIndex, etc.)
Demonstrated ability to ship production-ready internal tools or SaaS integrations
Strong problem-solver who can translate messy business requirements into clean technical solutions
Excellent collaboration and communication skills with technical and non-technical stakeholders
Bias for action and ability to thrive in ambiguity—comfortable experimenting and iterating in a fast-paced environment

Responsibilities

Design and build full-stack AI solutions (front-end, back-end, and integrations) to support GTM and internal teams
Develop agentic AI systems that automate complex workflows (e.g., pipeline forecasting, knowledge retrieval, reporting, customer engagement)
Engineer data pipelines and integrations with enterprise SaaS platforms (Salesforce, Snowflake, Looker, Jira, Slack, etc.)
Leverage GCP or AWS cloud infrastructure to deploy scalable, secure, and cost-efficient solutions
Partner with GTM stakeholders to identify and prioritize high-value problems, then rapidly prototype and iterate on solutions
Apply data engineering best practices to ensure high-quality, accessible, and actionable data across business functions
Collaborate cross-functionally with product, data science, and operations to evangelize internal AI adoption and best practices
Thrive in a scrappy, startup-style environment: experiment, learn fast, and deliver impact without waiting for perfect conditions

Skills

Agentic AI

Full-Stack Engineering

GCP

AWS

Data Engineering

Data Pipelines

Salesforce

Snowflake

Looker

Jira

Slack

Zefr

Contextual advertising technology for brands

About Zefr

Zefr focuses on contextual advertising, helping brands place their ads alongside relevant content without using personal information. Their technology is especially effective for video ads on platforms like YouTube and Facebook, allowing brands to reach specific audiences while maintaining user privacy. Zefr's Contextual Data Management Platform organizes brand preferences to deliver targeted ad campaigns with high engagement rates. The company differentiates itself by prioritizing privacy-compliant advertising, making it a valuable partner for brands looking to optimize their digital marketing efforts.

Los Angeles, CaliforniaHeadquarters

2009Year Founded

$63.1MTotal Funding

SERIES_ECompany Stage

Data & Analytics, EntertainmentIndustries

201-500Employees

Risks

Emerging AI technologies may increase competition in contextual advertising.

Reliance on platforms like YouTube and Facebook exposes Zefr to algorithm changes.

Expansion into new platforms like Snapchat may pose integration challenges.

Differentiation

Zefr specializes in privacy-compliant contextual advertising, avoiding personal information usage.

Their Contextual Data Management Platform offers impression-level transparency for ad campaigns.

Zefr's Atrium suite provides transparency in walled gardens like Meta and TikTok.

Upsides

Growing demand for privacy-compliant ads aligns with Zefr's contextual advertising approach.

Expansion into Snapchat's ad ecosystem enhances Zefr's brand safety measurement capabilities.

Promotion of Jon Morra to Chief AI Officer boosts AI-driven content analysis.

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