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Atlan is building the context layer for enterprise AI—infrastructure that helps enterprises deploy AI successfully by ensuring AI systems understand business context around data. Gartner has named Atlan a Leader across data catalogs, data governance, and metadata management, and one of three vendors building context graphs for AI agents.
In this Senior Sales Engineer role for North America, you will own the technical win on Atlan's most strategic enterprise deals, partnering closely with Account Executives. You'll conduct discovery across AI teams building agents, data platform teams, and enterprise architects—often within the same deal. Your focus is on solutions that prove real value in production, not just in demos. You'll be hands-on building POCs, demos, prototype agents, and your own tooling; managers here ask "what did you build this week?" You'll need to keep pace as the category, the Agentic Development Lifecycle, and the product evolve week to week.
Atlan is remote-first and global, with teams across 15+ countries. The company offers competitive compensation benchmarked at market top, performance-based variable pay, and equity. Benefits include day-one health, dental, vision, and mental health coverage, flexible time off, and a trust-first, async environment.
REQUIREMENTS:
- 5+ years of experience, including time in a customer-facing technical role (Field Development Engineer, Sales Engineer, Solutions Architect, or founding engineer)
- Practitioner background in data science, ML, or data engineering—you've lived the problems your buyers face
- Recent hands-on work with LLMs and agents; understanding of how agents retrieve data and use context
- Builder mindset: you want to be in front of customers during the sales cycle, not just on long post-sales builds
- High agency, comfort with ambiguity, and good judgment on what's worth building
BONUS:
- Founding SE or FDE experience, or time at an early-stage AI or infrastructure startup selling into enterprise
- Experience with vector databases, retrieval, or semantic layers
- Career that has crossed sides (e.g., data science at an enterprise, then customer-facing role at an AI vendor)
