Staff Applied AI Scientist: LLM & Agentic Systems

Demandbase; United States; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Demandbase is hiring an Applied AI Scientist (Staff level) to pair deep research with production capabilities. You will tackle hard reasoning, retrieval, and orchestration problems, delivering research-informed product work with prototypes as a starting point.

Preference is for SF Bay Area candidates in a hybrid environment. You will work closely with product and engineering, shaping scalable AI solutions for GTM and ABM use cases.

Qualifications

• PhD required or equivalent in a relevant field.
• 7+ years in applied ML, NLP, IR, or ranking with hands-on ownership of LLM and agentic systems.
• Shipped LLM/RAG-style systems into production with reliability, latency, and monitoring.
• Experience with tool use, routing, planning in multi-step orchestration.
• Strong coding ability in production-grade code.

Responsibilities

• Design grounding and context assembly: retrieval pipelines, context selection, query understanding.
• Improve orchestration and reasoning across multi-step workflows: tool use, routing, decomposition, evaluation.
• Build structured representations that help the system reason over accounts, people, and activity.
• Translate research into production-ready capabilities with engineering collaboration.
• Raise technical rigor: share patterns, mentor, and accelerate decisions across teams.

Skills

Deep learning

Research to production

Python

Production code

Mentoring

Education

PhD in CS, ML, NLP, IR, or related field

Job description

Demandbase is hiring an Applied AI Scientist (Staff level) to pair deep research with production capabilities. You will tackle hard reasoning, retrieval, and orchestration problems, delivering research-informed product work with prototypes as a starting point.

Preference is for SF Bay Area candidates in a hybrid environment. You will work closely with product and engineering, shaping scalable AI solutions for GTM and ABM use cases.