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# Senior Backend Engineer (Python)

- **Company:** Recruiting from Scratch
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $180,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Automation of Tests, Software Debugging, Python (Programming Language), NoSQL, Software Architecture, Software Engineering, SQL Databases, Systems Integration, Web Applications, Data Logging, Scripting, System Availability, Large Language Models, Prompt Engineering, Backend, Fastapi, Kubernetes, Web Api, Microservices
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-backend-engineer-python-san-francisco-ca--5bc996f8-5d45-4b5c-a6a4-9e21fcb8959c

## About the Role

Software Engineering, Python Programming/Scripting Language, Software Engineering, Python Programming/Scripting Language, Administrative Skills, Funding, Customer Support/Service, Artificial Intelligence (AI), Call Centers, Startup, * 5+ years of experience writing Python, with a strong focus on async web applications using FastAPI.

 * Proven experience in backend architecture, microservices, and designing scalable systems.
 * Strong understanding of integrating LLMs, external APIs, and managing complex stateful systems.
 * Demonstrated ability to solve hard technical problems and communicate effectively with cross-functional teams.
 * Experience with AWS and Kubernetes is beneficial, but Python expertise is paramount.

Preferred

 * Familiarity with CI/CD pipelines and automated testing frameworks.
 * Experience in a startup environment, showcasing grit and the ability to thrive under pressure.

## Description

* Build and maintain Python-based state systems that drive voice AI interactions across complex, real-time conversations.
 * Integrate and orchestrate multiple LLM providers, including prompt design and routing for seamless user experiences.
 * Write clean, high-performance Python code leveraging asyncio and best practices for maintainability.
 * Develop automated tests and validation suites to ensure system resilience and correctness.
 * Monitor production systems, debug agent behavior, and continuously improve reliability and conversation quality.
 * Design and optimize database schemas while operating both SQL and NoSQL databases in production.
 * Implement comprehensive metrics, logging, and alerting to maintain high availability and detect issues early.