Jobs at Aslan

Serve as Aslan’s first business operations hire, owning unassigned functions such as finance operations, vendors, contracts, insurance, registrations, compliance deadlines, onboarding, tooling, documentation, and internal processes. The role provides operational support for hiring, office logistics, security, partner-facing setup, and national security pilots while building scalable systems and ensuring urgent work is executed reliably.

Build autonomous AI agent systems for national security applications, including cognitive architectures, multi-agent orchestration, memory, planning, post-training, fine-tuning, evaluation frameworks, and deployment optimization. Own feedback loops from operational data and collaborate with platform and forward-deployed engineers. The role requires production-grade software and ML systems expertise, extended-horizon agent experience, model optimization skills, and sensitivity to adversarial or classified environments.

Build and deploy production software directly with customers in sensitive operational environments. Responsibilities include developing custom integrations, AI agent configurations, analytics, and operator workflows; debugging live agent behavior; adapting the platform to mission-specific needs; and feeding deployment insights back to core engineering. The role requires full-stack engineering, AI/ML understanding, self-direction, regular travel, and extended customer-site work in the DMV region.

Lead government growth by converting operational traction into validated requirements, execution-year funding, acquisition awards, and recurring out-year program lines. Own programming inputs, unfunded requirement justifications, reprogramming packages, requirement documentation, acquisition pathways, congressional engagement, and transition roadmaps across defense, intelligence, and federal law enforcement customers. The role requires personally transitioning capabilities from no requirement or funding vehicle through contracting, expansion, and programmed recurring funding.

Own evaluation quality for autonomous LLM agents deployed in national security environments. Operate the platform, investigate failures, build labeled datasets and regression suites, distinguish model errors from harness issues, develop simulation tooling, and define metrics for agent durability and progress across builds. The role requires production evals experience, strong Python, statistical judgment, familiarity with agent internals, and experience with preference data, process supervision, or reward modeling.