About Us

Since 2013, we’ve been building a CRM that gets out of your way and helps your team sell more, faster. Now we’re building AI into every part of it, so Close does the busywork and your team does the selling. No manual data entry, no 10-click workflows. Just communication-first, AI-powered sales software designed to help you succeed and scale.

We're bootstrapped and profitable which means we answer to our customers and play by our rules. We're proud of our 120-person, 100% remote team, focused on building Close so that no small, scaling business fails because it can't figure out sales.

Our Stack

Our backend tech stack consists primarily of Python Flask web apps with our TaskTiger scheduler handling many of the backend asynchronous task processing chores. Our data stores include MongoDB, PostgreSQL, Elasticsearch, and Redis. The underlying infrastructure runs on AWS using a combination of managed services like EKS, MSK, RDS and ElastiCache and non-managed services running on EC2 instances. We have CI/CD pipelines that build Docker images, run automated tests and deploy to Kubernetes clusters. We also use these images in our local development environment allowing coding locally against all of our services. We have a well-documented public API that is consumed by our front-end JavaScript app as well as numerous integrations. Our infrastructure is heavily automated using Terraform, Ansible and other AWS tools.

We love open sourcing our code and ideas on our GitHub and on The Making of Close, our behind-the-scenes Product & Engineering blog. Check out our open source projects like SocketShark, TaskTiger, LimitLion and ciso8601.

AI is both how we build and what we ship, and that's reshaped what engineering looks like. This is a transformation we’re embracing and find deeply exciting.

About the Role

The CRM team owns the surface Close customers live in all day: leads, contacts, opportunities, tasks, activities, custom objects, and the search that makes any of it findable. Everything upstream — calls, emails, meetings — flows into the data this team structures, and everything downstream, including every agent we ship, depends on it.

The team is making significant strides on the next iteration of Close's core data model, the largest engineering effort underway at the company.

We're reopening assumptions made a decade ago and asking what a modern CRM's data model should actually be — one where any small, scaling business can map their operations into Close their way. This is a long series of migrations and rearchitecture projects. The first of them are already underway. If you like greenfield and you like hairy, this is both at once: help design the next version of Close, and untangle the current one to get there.

One thing to know up front: we do move people between teams as the work shifts. Most engineers here end up on more than one team over their time at Close — this team is where you'd start, but over time you'll likely have the opportunity to work on many different projects.

You are

• 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 each ship on their own.

• Drawn to data model and retrieval problems. Schemas, relationships, normalization, query design, type systems. The plumbing that decides whether a CRM feels fast or feels like a database someone left running.

• Experienced in search — a serious bonus. Elasticsearch especially, and anything adjacent: Lucene internals, query planning, relevance, indexing at scale, building or operating a search engine rather than just calling one.

• 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 still 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.

• 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.

You will

• Rearchitect the core CRM data model. Rework how leads, contacts, opportunities, and custom objects relate to each other so customers can represent their business the way it actually works.

• Make Close genuinely 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 again: any MCP-compatible harness should be able to traverse, filter, and reason over a customer's CRM without learning our private query language first.

• Ship AI-native CRM features. This team built agentic enrichment: instead of paying a third-party data provider, an agent goes and researches whatever field you need, in bulk or automatically inside a workflow. There's a lot more of this ahead, including AI-powered data cleaning and richer AI search.

• Keep the hot paths fast. Finding a lead, updating a deal, scanning a pipeline, running a bulk action. Salespeople do these hundreds of times a week, and no amount of clever architecture matters if they're slow.

Tech you'll touch: Python, Flask, FastAPI, MongoDB, Elasticsearch, PostgreSQL, Redis, TaskTiger, MCP — plus whichever LLM ships next.

Benefits

• Compensation: Competitive pay plus an organization-wide goal-based bonus

• Paid Time Off: ~5 weeks of PTO to start. Plus a 1-week all-company Winter Holiday Break and paid US holidays. You'll earn 2 extra days for every year you're with Close.

• 80% Work Option: Work with your manager to choose between a standard 5-day week or a 4-day week at 80% pay

• Parental Leave: Paid leave for primary and secondary caregivers

• Sabbatical: A 1-month paid sabbatical every 5 years with the team

• Healthcare (US residents): Two medical plans with Close covering 99% of your premium, plus Dental, Vision, HSA, FSA, and company-paid Long-Term Disability

• 401k (US residents): We match your contributions up to 6%, vested immediately

Our Values

Build a house you want to live in - Examine long-term thinking and action

No BS - Practice transparency and honesty, especially when it’s hard

Invest in each other - Build successful relationships with your coworkers and customers

Discipline equals freedom - Keep your word to yourself and others

Strive for greatness - Constantly challenge yourself and others

Learn More

Listen to our CEO and Founder, Steli Efti, tell the story of Close’s journey in the $0-30m Blueprint. 

Watch our culture video from our 2023 team retreat in Milan. Every year our entire team gathers in person to build connection, foster cross-functional collaboration, and have fun. In 2027, we're headed to Dusseldorf, Germany!

Explore our product. Check out a demo!

Our Hiring Process

We ask a few role-specific questions as part of our application process. These questions are designed to help us learn more about you from the start, so please answer each one thoughtfully. We see this as an opportunity to get to know you beyond your resume.

We use AI tools daily at Close and expect candidates to do the same. In evaluating your application, we aim to get a sense for you - the way you think, how you communicate, the work you've done. Applications that read as fully AI-generated will not be considered.

Regardless of fit, you can expect to hear back from our team with an update on the status of your candidacy.

If you progress to the interview process, you'll receive a full outline of the role-specific steps in your first touchpoint with us. We do our best to make the hiring process clear and human.