[All remote jobs](https://jobicy.com/jobs.md)Open role[![Close logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2020/09/Closeio.png)](https://jobicy.com/company/close.md)Remote opportunity at[Close](https://jobicy.com/company/close.md) # Senior Software Engineer – Backend (USA Only – 100% Remote) Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/close.md)Share21 Aug 2026Published22Listing views2Application actions20 Sep 2026Apply before Opportunity details ## About this role. AI SummaryClose is hiring a senior backend engineer to build and operate core CRM, communications, growth, or agent-platform capabilities in a fully remote US-based team. The role centers on Python services and production systems running on AWS, Kubernetes, MongoDB, PostgreSQL, Elasticsearch, Redis, and asynchronous processing infrastructure. Candidates need demonstrated experience shipping reliable LLM-backed product features, designing public APIs, and handling customer-impacting operational incidents. The position favors pragmatic, fast iteration, independent ownership, and collaboration across shifting product teams. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior-level production engineering role spanning distributed backend systems, public APIs, cloud infrastructure, and customer-facing AI capabilities. Success requires sound technical judgment under operational constraints as well as the ability to independently ship and evolve ambiguous product work. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$170,000US market range$145k–$210k0$231k AI insightNo numerical compensation range is disclosed; "Competitive pay" and a goal-based bonus are not sufficient to extract actual salary. Estimated US-market annual base salary for a senior backend engineer with production AI, distributed-systems, and AWS/Kubernetes experience is $145,000-$210,000 USD, with an estimated midpoint of $170,000 USD. This is a market estimate, not an offer from Close. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[Flask](https://jobicy.com/jobs?search_keywords=Flask.md)[Backend Engineering](https://jobicy.com/jobs?search_keywords=Backend%20Engineering.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md)[Distributed Systems](https://jobicy.com/jobs?search_keywords=Distributed%20Systems.md)[LLM Applications](https://jobicy.com/jobs?search_keywords=LLM%20Applications.md)[API Design](https://jobicy.com/jobs?search_keywords=API%20Design.md)[MongoDB](https://jobicy.com/jobs?search_keywords=MongoDB.md)[Terraform](https://jobicy.com/jobs?search_keywords=Terraform.md) Sample interview questionsDescribe an LLM-backed feature you shipped to production and how you made its output dependable for users.I would explain the user workflow, model and retrieval design, and the specific guardrails used, such as structured outputs, validation, confidence thresholds, fallbacks, evaluations, and monitoring. I would also quantify adoption, quality, latency, or business impact and describe how production feedback informed iteration. How would you design an internet-facing API that must serve both a web application and external AI agents? I would start with clear resource and action boundaries, stable versioning, consistent authentication and authorization, idempotency for write operations, and explicit error contracts. For agents, I would provide concise schemas, discoverable documentation, scoped permissions, auditability, rate limits, and safe confirmation patterns for consequential actions. Tell us about a production incident involving latency or reliability. What did you do? I would first establish impact and stabilize the service through rollback, traffic controls, degradation, or capacity changes. Then I would use metrics, traces, logs, and recent-change analysis to identify the cause, communicate status clearly, and finish with a blameless postmortem and concrete prevention work such as alerts, load tests, or architecture changes. How would you approach scaling a CRM workload involving billions of MongoDB documents and Elasticsearch search? I would begin by profiling the access patterns, query shapes, index health, and service-level objectives. Likely approaches include targeted indexes, pagination and cursor patterns, asynchronous indexing, backpressure, shard and partition strategy, data-retention policies, and rigorous consistency rules between the source of truth and search index. How do you balance fast feature delivery with maintainability in a senior engineering role? I deliver the smallest useful version with clear acceptance criteria, instrumentation, and a reversible rollout plan. I protect critical interfaces and operational safeguards up front, document important tradeoffs, and schedule follow-up improvements when evidence shows they are warranted. ### 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](https://stackshare.io/close-crm/close) consists primarily of Python Flask web apps with our [TaskTiger](https://github.com/closeio/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](https://developer.close.com/) 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](https://github.com/closeio) and on [The Making of Close](https://making.close.com/), our behind-the-scenes Product & Engineering blog. Check out our open source projects like [SocketShark](https://github.com/closeio/socketshark), [TaskTiger](https://github.com/closeio/tasktiger), [LimitLion](https://github.com/closeio/limitlion) and [ciso8601](https://github.com/closeio/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. ### Our Teams When you apply, you’ll have an opportunity to highlight the team that appeals to you the most. We’ll do our best to honor this preference, but we’ll also be evaluating skillset fit and the needs of the business. 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’ll start, but over time you’ll likely have the opportunity to work on many different projects. The work splits roughly like this. Pick the team that excites you most: * Agents. Build Close’s agentic platform and customer-facing AI experiences. Voice Agents, Custom Agents, and Ask Chloe are already in flight. You’d work on the shared intelligence and orchestration layer that powers AI-driven processes across the product. That includes the ecosystem around our APIs and MCP surface, which enables external agents like Claude and ChatGPT to operate Close. This team is pushing deeper into applied AI, retrieval, and agent infrastructure more than ever before. * Communications. Own the voice, SMS, and email infrastructure powering Close — Twilio, WebRTC, WebSockets, AssemblyAI, ElevenLabs, and more. You’ll help build our voice, messaging, and conversational AI agents while scaling real-time AI across calls, email, and calendar sync infrastructure. * CRM. Build the structured context layer that humans and agents both depend on. We’re rebuilding the data model so it flexes with real businesses, making the CRM agent-ready (retrieval, traversal, action coverage through MCP and our public API), and shipping the next generation of AI-native CRM features (AI Enrich, Autofill, AI Search). Operating on billions of Mongo documents with Elasticsearch underneath. * Growth. Run the experiments and own the billing infrastructure that turn trials into paid customers. Stripe metered billing, AI credit top-ups, the activation and conversion funnel, and the team’s biggest bet right now: agentic onboarding (an agent that walks new customers through setup, configuration, and first comms). Hypothesis-driven, metric-first. ### 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 problem rather than retreating to what you know. You’ve seen a variety of problems, can collaborate and self-direct. * Building AI. You’ve shipped LLM-backed features for real users and have a POV on where they’re trustworthy, where they fall over, and how to get them production-ready when customers bet revenue on the output. We use Pydantic, Temporal, LangFuse, and other modern AI infrastructure tooling to power our agent platform. * 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 the use of AI tools (Claude Code, Codex and other best-in-class developer tools) and treat learning and experimentation as part of the work. * A builder first. You’d rather get the first iteration of a feature in front of fifty customers than spend three weeks fretting over a perfect PR. You ship. * Opinionated about API design for modern software. You’ve shipped internet-facing APIs and you think about who’s on the other end – apps, agents, humans poking around in docs – and what each of them 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. ### 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](https://www.close.com/blueprint). Watch [our culture video](https://www.youtube.com/watch?v=maXKi1GN2MI) 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](https://www.close.com/demo-site)! ### 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. Show more [Apply now >](https://jobicy.com/jobs/151308-senior-software-engineer-backend-usa-only-100-remote.md) > Annual salary information is not provided for this position. 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