Staff AI Software Engineer

🇺🇸 San Francisco, CA
$2K - $3K Annual
Posted 6 months ago
Expires June 9, 2026

Introduction to Demandbase:

Demandbase is the only pipeline AI platform that empowers GTM teams to automate growth at scale. With a unified view of data, insights, actions, and outcomes, B2B enterprises can seamlessly align and execute their account-based GTM strategies with confidence. Thousands of businesses trust Demandbase to maximize revenue, minimize waste, and consolidate their data and tech stacks – all in one platform.

As a company, we’re as committed to growing careers as we are to building world-class technology. We invest heavily in people, our culture, and the community around us. We have also continuously been recognized as One of The Best Places To Work in the San Francisco Bay Area by Fortune, and One of The 60 Best Companies To Sell For by Selling Power. Our offices are located in San Francisco, New York, Austin, Seattle, India, and the United Kingdom.

ABOUT THE ROLE

As a Staff AI Software Engineer, you will help architect and deliver AI-native platforms that shape how Demandbase builds and scales intelligent systems. You’ll play a key technical leadership role as we evolve from traditional SaaS patterns toward more autonomous, agent-driven capabilities powered by generative AI.

This is a Staff-level individual contributor role with broad influence across multiple teams. You will partner closely with Product and Engineering leadership, contribute to architectural direction, and help ensure our platforms can support large language models (LLMs), agentic workflows, and real-time AI-driven capabilities at scale.

RESPONSIBILITIES

CORE ENGINEERING

- Design and build scalable, cloud-native microservices that support LLM-powered experiences, agentic workflows, and real-time AI data synthesis.

- Contribute to the technical roadmap for AI-native systems aligned with the company’s AI-first product strategy.

- Build and operate production-grade AI/ML systems, including RAG (Retrieval-Augmented Generation) pipelines and vector search architec...

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