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Senior Backend Engineer – Backend Platform (USA Only, 100% Remote)

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Remote from
USA
Salary
USD 140k–210k / yr
Employment
Full Time
Experience
Senior
Published
Apply before
2 Nov 2026
Listing views
82
Application actions
4
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AI Summary

The role, at a glance.

Close is hiring a Senior or Staff Backend Engineer to help establish its new Backend Platforms team. The role focuses on developer-facing platform foundations, including API conventions, authorization, observability, database safety, eventing, and framework modernization. The engineer will also expand AI development tooling such as cloud development environments and agent-assisted review and root-cause workflows. This is a high-influence remote US role requiring deep Python expertise, production systems experience, and demonstrated delivery of LLM-backed or agentic products.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThis is a senior-to-staff-level platform role with broad ownership across foundational backend systems, production reliability, and AI developer tooling. Success requires making durable technical decisions, influencing multiple product teams, and safely operationalizing coding agents in a fast-moving environment.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$175,000
US market range$150k–$230k
AI insightThe disclosed yearly base salary range is USD 140,000–210,000, producing a midpoint of USD 175,000. A competitive US market estimate for a senior backend/platform engineer with Python, cloud infrastructure, observability, and AI-platform responsibilities is approximately USD 150,000–230,000 annually; actual pay may vary by level calibration between Senior and Staff and candidate experience.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
Describe a platform capability you built that made other engineers more productive.

I would explain the developer problem, the baseline friction or adoption data, and the smallest useful platform solution I shipped. I would cover how I established opinionated defaults, documentation and migration support, then measured adoption, reliability, and the reduction in repetitive implementation work.

How would you approach migrating backend services from Flask toward FastAPI without disrupting product delivery?

I would begin by defining compatibility requirements for authentication, error handling, telemetry, deployment, and API contracts. I would introduce a supported migration path with shared middleware, templates, examples, and incremental service-by-service adoption, using contract tests and production metrics to manage risk rather than forcing a rewrite.

What guardrails would you implement before allowing an AI coding agent to approve pull requests?

I would scope autonomy by change risk and require deterministic checks such as static analysis, formatting, dependency and security scanning, targeted tests, and protected-path rules. I would add audit logs, confidence thresholds, rollback mechanisms, sampling-based human review, and progressively expand permissions only after measuring false approvals and incident outcomes.

Tell us about an incident where you improved observability rather than only fixing the immediate symptom.

I would describe the customer impact, diagnosis process, and immediate mitigation, then explain how I added actionable metrics, tracing, alerts, dashboards, and ownership boundaries. The outcome should demonstrate that the same failure mode became easier to detect, diagnose, and prevent for all teams.

How do you design an internet-facing API for both human developers and AI agents?

I would prioritize stable resource modeling, consistent authentication and error semantics, idempotency where appropriate, pagination, rate-limit behavior, and versioning discipline. I would pair the API with accurate OpenAPI documentation, examples, machine-readable schemas, clear permission boundaries, and telemetry that reveals integration failures without exposing sensitive data.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

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

Close runs on Python: Flask web apps, TaskTiger, billions of MongoDB documents, a public REST API that customers and external agents both build on. Four product teams ship features on top of that every week. Backend Platforms owns the foundation underneath it all.

As an Engineer on our Backend Platforms team, you’re building for other engineers. When a product team adds a new API endpoint, most of what they write isn’t their feature — it’s wiring: authentication, permissions, rate limiting, the shape the endpoint has to take so it looks like every other endpoint when you squint. Multiply that across telemetry, eventing, database migrations, authorization, and local development, and you get the problem this team exists to solve: make the paved road faster to walk than the trail.

The other half of the team’s mandate is the AI development platform. We’ve built DevDawg, cloud-based development environments preconfigured for our entire application stack and our engineering practices, and Spice, our extension layer on top of a coding agent that runs internal review workflows and root cause analysis. Spice is hooked into GitHub and can already approve mergeable pull requests on its own for simple changes. This team is responsible for expanding what it can safely handle.

This is a new team. You would be one of the first hires, and you’d have unusual influence over what the team owns and how it operates.

One thing to know: 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.

This role is open at the Senior and Staff levels. You don’t need to pick one when you apply: we’ll calibrate together during the process.

You are

  • A seasoned Python engineer. Python is our backbone and it matters in this role more than on other teams at Close. Architectural patterns don’t port cleanly between languages, and you’ll be setting the patterns. Go, Rust, or TypeScript alongside it is welcome.

  • Drawn to meta-problems. This team doesn’t ship features to customers; it changes how features get built.

  • AI-native in production. You’ve shipped meaningful LLM-backed or agentic work to real users. For a team building AI tooling that other engineers depend on, this is foundational to the role.

  • Working with AI in your day-to-day. You use coding agents in your own workflow and have a real POV on where they help and where they get in the way. On this team, your POV becomes the product. We fund best-in-class developer tools and treat experimentation as part of the work.

  • Fluent in observability and production practice. Telemetry, metrics, tracing, alerting, Sentry ownership, what production-ready actually means. You’ve been the person who made a system legible when it broke.

  • Opinionated about API design. You’ve shipped internet-facing APIs and you think about who’s on the other end — apps, agents, humans reading docs — and what each needs.

  • 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 rough v1 in front of five engineers than spend three weeks on abstractions.

  • Energized by internal customers. Your users are a Slack DM away. You’ll talk to them directly instead of through a PM, and you’ll use most of what you build yourself.

You will

  • Expand DevDawg and Spice. Cloud development environments for our full stack, paired with automated review and root-cause tooling that can approve real pull requests. Making that safe enough to cover more of our review surface is one of the team’s biggest projects.

  • Build the paved roads for our API layer. REST blueprints, GraphQL schema, OpenAPI, realtime, and the auth and permission plumbing that every endpoint needs. Consistent patterns are what make shared utilities possible.

  • Modernize the backend framework layer. Web and async compute frameworks, performance, and migration paths (Flask → FastAPI, among others) — with clear defaults, examples, and migrations teams can adopt without asking permission.

  • Own how we see production. Observability, metrics, alerting, and the readiness bar teams meet before shipping. When the same issues keep showing up in incident reviews, you make sure the underlying cause gets owned rather than re-triaged.

  • Ship shared backend services and primitives. Eventing patterns and the event log, database-change safety and migration guardrails, delegated access and auditability, the internal admin framework and support-facing APIs.

  • Set the guardrails for coding agents in our backend. Static analysis, linting, hooks, test harnesses — the constraints that make agent-written code safe to merge at volume.

  • Partner across the org. Infrastructure owns the substrate (AWS, Kubernetes, datastores); you own the application layer on top.

Tech you’ll touch: Python, Flask, FastAPI, GraphQL, TaskTiger, Rust, Typescript, Kafka, Redis, MongoDB, PostgreSQL, Elasticsearch, Docker, Kubernetes, GitHub Actions — plus whatever coding agent 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.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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