The opportunity
The CRM team owns everything that Close’s customers touch all day, every day: leads, contacts, opportunities, tasks, activities, custom objects, and search. Each time a call is logged, an email is threaded, a meeting is summarized, it lands on the record this team owns, and every agent we ship starts there.
What you'll do
A seasoned engineer. Python is our backbone, but perhaps you've worked across: Go, Rust, or TypeScript. You pick the right tool for the workload rather than retreating to what you know.
Architecturally minded. This is the thing we care about most. You've designed: systems others built on, planned a migration that couldn't take the product down, and know how to sequence a rearchitecture into pieces that ship independently.
Drawn to data model and retrieval problems. Schemas, relationships,: normalization, query design, type systems. The plumbing decides whether a CRM feels fast and we pride ourselves on being fast.
Experienced in search: this is a serious bonus. Elasticsearch especially, and anything adjacent: Lucene internals, query planning, relevance, indexing at scale, building or operating a search engine.
AI-native in production. You've shipped meaningful LLM-backed or agentic: features to real users, and you have a POV on where AI earns its place in a CRM workflow and where a structured system wins.
Working with AI in your day-to-day. You use AI tools in your own workflow to: ship faster, write tighter code, and reason about unfamiliar parts of the codebase. We fund best-in-class developer tools and treat experimentation as part of the work.
What they're looking for
- Battle-tested. You've debugged incidents where latency budgets didn't hold,: owned a system everyone else relied on, or carried a pager for something with real customer impact.
- A builder first. You'd rather get a sloppy v1 in front of fifty customers: than spend three weeks on abstractions. You ship.
- Rearchitect the core CRM data model. Rework how leads, contacts,: opportunities, and custom objects relate to each other so each of our customers can represent their business the way it operates.
- Make Close usable by agents. The Agents team builds the MCP foundation; we: build the tools and endpoints on top of it that expose the CRM's data and actions. The hard part is search: any MCP-compatible harness should be able to traverse, filter, and reason over a customer's CRM without learning our private query language first.
