> Markdown version of [/jobs/ext/3309679-backend-software-engineer-genai](https://www.wearedevelopers.com/jobs/ext/3309679-backend-software-engineer-genai). 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). --- # Backend Software Engineer - GenAI - **Company:** The Arena Corporation - **Location:** Seattle, WA, United States - **Experience:** Experienced - **Salary:** $180,000.0 - $230,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computing Platforms, Code Review, Distributed Systems, Software Deployment, Software Engineering, Systems Integration, AI Infrastructure, Large Language Models, Model Validation, Backend, Kubernetes - **Published:** September 20, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=78b1609ce035acbf ## About the Role * 4+ years of experience in software engineering, with a strong backend foundation - distributed systems, APIs, production-grade software * Hands-on experience building GenAI systems: vector databases, LLM integration, RAG architectures, and evaluation harnesses for LLM output * Familiarity with tool routing, tool-call validation, and common LLM failure modes * Understanding of the science underlying the systems you build - not just how to wire them together, but why they work and where they break * Background at an AI-native company, or a clear transition from backend engineering into AI specialization * Strong sense of ownership and a bias for action Bonus Points: * Experience with fine-tuning or model evaluation workflows * Familiarity with AI infrastructure: embedding pipelines and inference optimization * Experience working on software in defense, aerospace, or other complex operational domains * Experience deploying software to production environments, including cloud (AWS, Kubernetes) and edge infrastructure ## Description Our client is revolutionizing military logistics and sustainment through the deployment of AI-enabled solutions. Combining elite Silicon Valley software expertise with deep operational experience working in and with the Department of Defense, our client builds cutting-edge software to solve the most critical logistics challenges faced by the U.S. military and its allies. Their flagship product is an advanced software platform that gives commanders a single, real-time operating picture of their sustainment operations - from inventory and distribution to medical and operational planning - even in degraded and contested environments. They stay close to their users by embedding directly with military units during exercises and rotations, shipping constantly based on what they learn in the field., Our client is seeking a Backend Software Engineer to join a high-impact team working at the intersection of advanced logistics algorithms, modern AI-enabled software, and complex systems integration - all in support of the warfighter at the tactical edge. This role sits within their AI agentic product layer, and you'll own the design and implementation of production GenAI systems that bring intelligent, autonomous capability to the sustainment domain. This is a backend engineering role first - they're looking for someone who has built real AI systems from the ground up, worked closely with engineers and operational experts, and cares about shipping software that actually works in the field. What You'll Be Doing: * Design, build, and deploy production-grade GenAI systems - including RAG architectures, vector databases, LLM integrations, and tool-call frameworks - in support of their AI agentic product layer * Build and maintain evaluation and testing harnesses to validate LLM output quality and catch regressions in production * Collaborate with the broader platform and product teams to integrate AI capabilities into core platform workflows * Participate in technical design discussions and code reviews, contributing to a culture of engineering rigor and mission focus * Triage and debug issues in production, ensuring reliability and rapid iteration in support of operational needs * Work closely with engineers, product managers, and military stakeholders to ensure AI systems meet real-world sustainment requirements