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# Senior Software Engineer

- **Company:** David Joseph & Company
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $311,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Databases, Cursor, Distributed Systems, Elasticsearch, Python (Programming Language), MongoDB, Ruby, Microsoft Copilot, Google Cloud, ReactJS, Large Language Models, Backend, Kubernetes, Apache Kafka, Terraform
- **Published:** October 23, 2026
- **Apply:** https://www.thejobnetwork.com/job/a0c0705a-a0a6-40ad-9664-ecc3c5716b25/senior-software-engineer

## About the Role

* 5-8 years in backend or full-stack engineering, centered on building large-scale distributed systems
 * Hands-on experience at a startup, an AI-native company, or in an early/founding-engineer setting
 * A track record of owning and operating high-scale distributed systems (100K+ users)
 * Clear growth in scope and responsibility over your career, rather than staying flat at the same level
 * Strong system-design ability for large-scale data and distributed systems
 * Currently at (or recently from) a well-regarded, high-growth engineering organization, with a strong database background or experience building LLM-powered systems
 * Comfortable working across Ruby/Rails, Python, and MongoDB or Elasticsearch
 * Based in the SF Bay Area and able to work hybrid, three days a week on-site

Nice to Haves

 * A CS degree from a strong program (weighted less heavily if you have 5+ years of strong experience)
 * Day-to-day use of AI-assisted development tools such as Copilot or Cursor

## Description

You'll design, build, and scale large distributed systems, owning significant pieces of the platform end-to-end and building AI-native agent systems that hundreds of thousands of customers rely on every day.

What you'll be doing

 * Own significant systems and features end-to-end, from design through production and day-to-day operation
 * Build and operate large-scale distributed systems, choosing and combining the right technologies for the problem
 * Take hard, ambiguous problems and drive them to shipped outcomes, owning reliability, performance, and cost
 * Build AI-native agent systems used at scale

Tech stack: React, Ruby/Rails, Python, MongoDB, Elasticsearch, GCP/K8s (with Kafka and Terraform in the mix)