> Markdown version of [/jobs/ext/3700766-staff-software-engineer](https://www.wearedevelopers.com/jobs/ext/3700766-staff-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Software Engineer

- **Company:** French & French, LLC
- **Location:** Santa Monica, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Databases, Distributed Systems, Elasticsearch, Github, PostgreSQL, Node.Js, Software Product Management, TypeScript, ReactJS, Amazon ElastiCache, Large Language Models, Backend, Agentic-AI, Cloudformation, Amazon Relational Database Service, Apache Kafka, Graphql, Terraform, Docker
- **Published:** October 12, 2026
- **Apply:** https://www.juju.com/job/16_f602a3441

## About the Role

* 7 to 25 years of full-stack engineering experience, with at least 5 years operating at a Senior level.
 * Strong, demonstrable TypeScript depth, ideally with recent, complex systems you've built hands-on and can talk through in detail.
 * Production experience with React, Node/Express (in Docker), GraphQL/Apollo, and PostgreSQL.
 * Experience scaling high-throughput distributed systems in the cloud, with AWS and infrastructure-as-code (Terraform or CloudFormation).
 * A background at a high-growth tech company where software was the actual product (VC-backed startup or FAANG), not a traditional industry running internal tools.
 * 2+ years of tenure and real progression within the companies on your resume.
 * A sharp eye for security risk, given the sensitivity of the data involved.
 * Nice to have: fintech background, familiarity with AI product development cycles (evals, experiment design, dataset curation), an SRE mindset, and an active GitHub or side projects.

## Description

* Architect, build, and ship multi-step AI agents that customers use to digitize mortgage ops workflows, saving them millions per year in manual processing.
 * Integrate with third-party lending APIs to generate documents and disclosures, produce automated underwriting results, and catch fraud before it hits a human reviewer.
 * Design and launch the next generation of job-processing infrastructure on AWS, focused on observability and reliability at scale.
 * Work directly in a codebase handling loan data with thousands of fields per record, so schema decisions have real downstream consequences.
 * Ship to production in week one. No multi-month onboarding runway, you're expected to contribute fast.
 * Mentor engineers earlier in their career, on both technical depth and judgment calls.
 * Own features end to end, from design through deployment, for enterprise mortgage lender customers.

Where it gets technically interesting

 * Nearly the entire codebase is TypeScript in a single monorepo, with types generated directly from Postgres and GraphQL schemas so a database change surfaces as a compile error in React components.
 * 100% of infrastructure has been managed in Terraform since day one, with automated per-PR staging environments, so nothing gets deployed by hand.
 * You're wrangling non-deterministic LLMs into systems that have to be reliable for a regulated, high-stakes financial process, not just a chatbot.
 * AWS backend runs on ECS, RDS, ElastiCache, Kafka, and ElasticSearch, with real throughput demands as loan volume scales.
 * The platform stores and displays highly sensitive personal and financial data, so security isn't an afterthought, it's baked into every schema and endpoint decision.
 * A comprehensive testing library mocks production-like data for end-to-end, integration, and performance tests, which is what lets the team ship fast without breaking uptime.