> Markdown version of [/jobs/ext/4635558-senior-software-engineer](https://www.wearedevelopers.com/jobs/ext/4635558-senior-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).

---

# Senior Software Engineer

- **Company:** The Fort, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $240,000 - $260,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Data Infrastructure, Data Security, Distributed Systems, Interoperability, Python (Programming Language), Machine Learning, Large Language Models, Backend, Kubernetes, Docker
- **Published:** November 8, 2026
- **Apply:** https://www.juju.com/job/28_25304_b97082ab70e3982a238de9e9dee7cf63

## About the Role

* 5-15 years of backend engineering experience, with strong depth in Python and distributed systems.
 * A proven track record shipping agentic services using LLMs into production.
 * Experience handling and securing large-scale, sensitive data.
 * Prior work in early-stage startups or entrepreneurial teams where autonomy is essential.

Technical Skills

 * Proficiency in Python/JS for ML development.
 * Hands-on experience with Docker, Kubernetes, and AWS infrastructure.
 * Strong understanding of data security, permissioning, and interoperability across AWS services.

Soft Skills

 * High ownership mindset and comfort operating in ambiguity.
 * Thrives solving hard technical problems in fast-moving environments.
 * Mission-oriented, collaborative, and proactive.
 * Ideally, we want candidates who have experience launching or owning early-stage products or working in early-stage startups.

## Description

* Build, deploy, and support mission-critical backend services powering a secure, AI-enabled data platform.
 * Launch agentic systems leveraging LLMs, embeddings, and inference into high-security production environments.
 * Design and maintain scalable infrastructure using Docker, Kubernetes, and AWS (S3, Lambda, RDS).
 * Work across the entire data stack - from ingestion and permissioning to deployment, monitoring, and lifecycle management.
 * Partner closely with founders and cross-functional stakeholders to translate complex intelligence problems into elegant engineering solutions.
 * Own major technical decisions and help set engineering standards as the team scales.