Job Opportunities API

At Zone 5 Technologies, we're redefining what's possible in unmanned aircraft systems. Our team of engineers and innovators is developing cutting-edge autonomous solutions that push the boundaries of UAS technology - solving complex challenges that matter. We're building the future of UAS capabilities, and we're looking for exceptional talent to join us. If you're driven by hard problems, energized by rapid innovation, and ready to make an impact on next-generation flight systems, you belong here. We are investing in in-house LLM tooling and are hiring a dedicated MLOps Engineer to help grow it. You will build AI-powered capabilities—retrieval-augmented generation, tool integrations, and agentic workflows—and turn them into reliable services used by teams across the company. This is a builder's role focused on shipping new capability.   The role spans a broad stack. We welcome both generalists and specialists—you do not need every skill listed below. Tell us where you are strong and where you want to grow. The center of gravity is LLM application development, retrieval quality, and agent design.   Responsibilities:   LLM Applications, RAG & Agents   Design and build new LLM-powered tools and agentic workflows that automate real work and improve productivity across the company   Extend and improve our RAG systems—ingestion, chunking, embedding, retrieval, ranking, and evaluation—to raise answer quality   Structure retrieval around the organization's information hierarchy so that relevance and access boundaries improve together   Build tool integrations that connect LLMs to internal systems and data sources   Design agents that act safely against real systems, with appropriate guardrails, human-in-the-loop where warranted, and clear failure behavior   Establish evaluation and testing frameworks to measure quality, catch regressions, and guide iteration   Partner with teams across the company to identify high-value use cases and turn them into deployed tools   Service Deployment & AI Infrastructure   Deploy AI tools and services for teams across the company, taking them from prototype to reliable production   Build and operate the infrastructure that hosts models, tools, and supporting services on Kubernetes   Manage model serving, inference endpoints, and the APIs and gateways around them   Implement monitoring, logging, and usage observability so we understand how tools perform and get used   Access, Security & Data Boundaries   Ensure retrieval and agent tools respect the same access boundaries as the underlying systems—no cross-team or cross-project data leakage   Integrate with existing identity and permission systems so tools honor who is allowed to see what   Apply data-handling practices appropriate to a defense environment   Treat access control as a first-class design concern in every tool, not an afterthought   Automation & Data Operations   Build CI/CD pipelines for AI tools, services, and agents   Automate provisioning and configuration with Ansible and infrastructure-as-code practices   Build data pipelines to ingest, transform, and index content for RAG and AI applications   Manage vector databases and other stores backing retrieval and AI workloads, including versioning and quality checks   Maintain reproducible environments across development, staging, and production   Qualifications:   Bachelor's in Computer Science, Software Engineering, Data Engineering, or related field – equivalent industry experience also welcome   3-6+ years of experience in MLOps, software, platform, or backend engineerin