Jobs at Demandbase

Own Demandbase’s corporate FP&A processes, including annual budgeting, rolling forecasts, long-range planning, integrated three-statement modeling, revenue and cash forecasting, variance analysis, scenario planning, and board-level reporting. The role validates financial models, coordinates inputs across finance and business teams, improves planning systems and processes, collaborates with Accounting, and mentors junior FP&A staff.

Runs paid search, paid social, AI SDR, and account-based demand-generation programs. Manages agencies, budgets, creative and audience testing, pipeline performance, attribution, and conversion reporting. Builds AI agents and no-code or low-code workflows using tools such as Claude, Clay, n8n, Zapier, and Demandbase to automate campaign QA, routing, enrichment, alerts, and reporting.

Leads the strategy, architecture, and operation of Demandbase’s internal developer platform and cloud infrastructure. Responsibilities include Kubernetes platform management across AWS and GCP, CI/CD and GitOps, infrastructure as code, service mesh, observability, FinOps, security, incident response, and AI-assisted development workflows. The role sets organization-wide technical standards, authors architecture guidance, leads major incidents and postmortems, and mentors senior engineers across teams.

Leads strategy, planning, execution, and optimization for B2B user summits, trade shows, and field events. Owns event portfolios, budgets, vendors, logistics, onsite production, cross-functional coordination, lead capture, sales follow-up, and pipeline measurement. Develops scalable event playbooks and processes while guiding team members, contractors, and agencies. Requires extensive B2B event marketing experience, strong project and budget management, revenue focus, stakeholder influence, and travel for events.

Own cloud security across AWS, GCP, Kubernetes, containers, virtual machines, and infrastructure-as-code environments. Investigate attack paths, assess IAM and architecture risks, review Terraform and CI/CD controls, prioritize Wiz findings, automate remediation, support cloud incidents, and drive issues to verified closure. The role also includes defining security metrics, influencing cross-functional engineering teams, mentoring engineers, and advancing secure-by-default cloud patterns.

Own Demandbase’s AI product adoption and growth strategy, guiding customers from discovery and activation through repeat usage, cross-capability adoption, consumption growth, retention, and commercial expansion. Define adoption funnels, meaningful value metrics, lifecycle strategies, experiments, packaging, entitlements, and monetization mechanics. Partner with Product, Analytics, Data Science, Finance, Sales, Customer Success, and Marketing to improve AI outcomes, establish behavioral insights, and turn successful experiments into scalable product experiences.

Owns customer relationships throughout the lifecycle, driving adoption, value realization, renewals, onboarding, and expansion for Demandbase solutions. Serves as a trusted advisor to senior marketing stakeholders, delivers ABM strategies and best practices, coordinates cross-functional initiatives, resolves customer issues, and leads technical or process-driven implementations. Develops customer success stories and maintains expertise in Demandbase products, industry trends, and competitive solutions.

Lead the strategy and roadmap for Demandbase’s orchestration platform, including workflow builders, triggers, actions, integrations, and AI-assisted automation. Partner with engineering to scale high-volume, low-latency event processing and support emerging agentic use cases. Drive platform extensibility, reliability, transparency, and user efficiency across enterprise GTM workflows.

Build and productionize machine learning and GenAI solutions for company and domain intelligence. Develop scalable data, feature, evaluation, and AI pipelines using NLP, LLMs, transformers, RAG, embeddings, and retrieval techniques. Own solutions from experimentation through deployment, monitoring, and support, using cloud-native infrastructure and strong software engineering practices. Improve model quality, reliability, latency, scalability, and cost across large-scale structured and unstructured datasets.

Build AI-native, production-ready user experiences from concept through launch using UX design, frontend engineering, and AI-assisted development. Partner with Design, Product, AI, and Engineering teams to create agentic interaction patterns, reusable components, workflows, tools, and guardrails. Improve design-to-production fidelity, usability, accessibility, performance, and quality while mentoring distributed teams and helping establish Demandbase’s UX Engineering practice.

Build and operate the shared LLM runtime: LLM gateway, cost controls, observability, evals infra, caching, and guardrails. Own reliability (SLOs, on-call, incident response), instrument systems, reduce LLM spend, and enable product teams to ship LLM features safely and efficiently.

The Applied AI Scientist will develop AI features, improve orchestration and reasoning systems, and work closely with engineering teams on production capabilities.

Lead and expand executive relationships with top technology and advisory partners. Develop joint product, AI and GTM strategies, drive partner integrations and co-selling, influence product roadmaps, run executive engagement and strategic planning, and coordinate cross-functional teams to deliver measurable business outcomes.