Demandbase is the only pipeline AI platform that empowers GTM teams to automate growth at scale. As a Staff Software Engineer, you will help architect and deliver AI-native platforms and play a key technical leadership role in evolving the company's systems towards more autonomous, agent-driven capabilities powered by generative AI.
Responsibilities:
- 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
- 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
- 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
Requirements:
- 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, Scala, or Python
- Experience with Kubernetes, container orchestration, and cloud platforms (AWS, GCP, or Azure)
- Experience with vector search / vector databases (for example Pinecone, Milvus, Weaviate) and AI infrastructure at scale
- Strong understanding of CI/CD automation and AI-augmented development workflows
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
- Strong communication skills and the ability to influence technical and non-technical partners