Staff AI Software Engineer

Staff AI Software Engineer 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 architectures. - Partner on architectural planning for AI agents, inference optimization, and scaling AI workloads (latency, reliability, and cost efficiency). - Establish and follow best practices for observability, resiliency, and cloud-native deployments in systems that include non-deterministic AI behavior. - Improve CI/CD automation and developer workflows, including practical use of AI-assisted engineering tools. LEADERSHIP & BUSINESS ACUMEN - Translate AI-first product direction into production-ready technical plans and platform decisions. - Partner with Product and Engineering leaders to connect AI platform work to measurable outcomes. - Lead and contribute to cross-team initiatives that span multiple engineering domains and platform layers. - Help set engineering standards for modern AI system design, balancing experimentation speed with operational discipline. - Stay current on emerging AI approaches and help the team apply what’s useful in a pragmatic, scalable way. COLLABORATION & MENTORSHIP - Collaborate with other Staff engineers across teams to integrate AI capabilities across the platform. - Provide guidance through design reviews, system-level discussions, and technical forums. - Mentor engineers on AI-native system design, distributed architectures, and scaling AI-heavy workloads. - Contribute to documentation, architectural standards, and internal knowledge sharing. - Help build a culture that values fast learning, high quality, and practical AI innovation. QUALIFICATIONS - 8+ years of professional software engineering experience, with 2+ years operating in a Staff-level (or equivalent) capacity. - Proven track record shipping complex systems beyond basic CRUD applications. - Strong expertise in distributed systems, system design, and performance optimization. - Hands-on experience building or deploying production AI/ML features using LLMs, agentic frameworks, or similar technologies. - Strong proficiency in Java, S ... (truncated, view full listing at source)