We9re hiring a Staff Backend Engineer on our Core team to design, build, and own the backend systems and APIs that power our platform. This is a senior individual contributor role with a Principal trajectory, meaning real architectural ownership, not implementation of someone else9s decisions.
The right candidate thinks in systems and consequences. You9ve owned backend platforms where the data was genuinely sensitive, you9ve made architectural decisions you had to live with, and you9re comfortable saying 44we should not do this44 when necessary. You write Python continuously and recently, you know AWS deeply, and you have strong opinions about reliability earned through experience.
What You9ll Do
- Design, build, and own production-grade REST APIs and backend services.
- Architect and maintain scalable, secure backend systems with clear ownership of trade-off decisions and long-term maintainability.
- Ensure high performance and responsiveness of applications across the platform.
- Collaborate with front-end developers and cross-functional teams to integrate user-facing elements with server-side logic.
- Mentor engineers and contribute to engineering standards, documentation, and architectural direction in a collaborative, low-ego environment.
- Troubleshoot and resolve production issues as they arise.
- Partner with Product, Security, and Data teams to translate ambiguous requirements into durable backend platforms.
- Make principled decisions about when architectural approaches are inappropriate, particularly in security- or compliance-sensitive areas.
Requirements
- Proven experience designing, building, and owning production-grade REST APIs at scale. You have been the engineer responsible for the full lifecycle. You have defined API contracts that other teams depend on, handled breaking change management, and built services that handle real production load. You have owned APIs, the decisions behind it, and everything that happened to it in production.
- Hands-on production experience with cloud infrastructure across AWS, GCP, or Azure. On AWS this looks like ECS, RDS, Lambda, S3, SQS, and IAM. On GCP or Azure, equivalent managed compute, storage, messaging, and identity services. Experience should be with enterprise-grade cloud platforms, not developer-tier or hobbyist hosting solutions.
- Demonstrated ability to make and own architectural decisions on production backend systems, including trade-off analysis and long-term maintainability. You have been the person in the room who decides how something gets built, not just the person who implements the decision. You can articulate why you made a choice, what you gave up to make it, and what you would change if you were doing it again. You think about what a system looks like two years from now, not just whether it works today.
- Proficient with recent, continuous production experience using Python as a primary language- not occasional scripting or secondary usage. Python has been your primary production language for at least five years and it is what you reach for first. You have built and maintained production backend services in Python, not just written automation scripts or contributed Python to a codebase that is primarily something else. FastAPI in production is required.
- Proficient in working with SQL databases in production environments. You write queries that perform well under real load, design schemas that hold up as requirements change, and understand how indexes, query plans, and connection pooling actually work in production. PostgreSQL is the primary database here and you should be comfortable with migrations, row-level security, and debugging slow queries when something goes wrong at 2am.
- Familiarity with CI/CD pipelines and tools including GitHub Actions, Jenkins, or equivalent. You have worked within them, understood how they affect your team9s ability to ship safely, and had a voice in how they are configured or improved.
- Demonstrated experience mentoring engineers and contributing to engineering standards, documentation, or architectural direction. You have made the engineers around you better- through code reviews, pair programming, design feedback, or documentation that actually gets used. At staff level, your impact extends beyond your own output. You have shaped how your team builds things, not just what they build.
- AI-native or AI-fluent- you use AI as a core part of how you plan, design, and build software, not as an occasional shortcut. Claude is preferred but any serious AI-driven engineering workflow counts. You have a genuine drive to keep learning how to use AI more effectively, both in engineering and beyond.
- U.S. Permanent Residency is required.
- Advanced proficiency in English: This role requires advanced proficiency in English to effectively communicate complex information with team members and stakeholders, and to complete job-related documentation and collaboration tasks. We welcome applicants from all backgrounds and are committed to providing reasonable accommodations where applicable.
Preferred Qualifications
- Hands-on experience building and deploying production APIs with FastAPI. You have worked with Pydantic models, dependency injection, async route handlers, and OpenAPI documentation in a codebase that real engineers or systems depend on.
- Experience with Kubernetes for container orchestration. You have deployed and operated services on Kubernetes in a production environment. You understand pod lifecycle, resource limits, health checks, and what it looks like when something goes sideways on a Friday afternoon.
- Production experience with PostgreSQL including schema design, query optimization, and migrations. You have designed schemas that survive changing requirements, written migrations that do not take down production, and sat with a slow query long enough to actually understand what the execution plan is telling you. You know when an index helps and when it makes things worse.
- Experience building systems that handle sensitive or regulated data, such as PII, PHI, or data subject to compliance frameworks like HIPAA, PCI-DSS, FedRAMP, or SOC2. You have worked somewhere that the stakes were real, not theoretical. You build access controls, audit logs, and data isolation because you understand why they matter, not because a compliance checklist told you to.
- AI tools are a genuine part of how you engineer. You use Claude, Cursor, Copilot, or something similar in PyCharm or VS Code as part of how you actually work every day, not as an occasional shortcut. You have developed a real opinion on where these tools accelerate good engineering and where they get in the way.
#LI-MH1 #nashville #hybrid
