• Develop tools, methodologies, and infrastructure to support Red Team engagements in a variety of cloud environments and novel platforms • Participate in security assessments against a diverse cloud environment and find vulnerabilities in software, systems, and networks • Set scope, objectives, and timelines for security assessments and leverage data to create meaningful metrics • Work with security and engineering teams to communicate findings, recommendations, and knowledge to key stakeholders • Play a critical role in building a Red Team that has a wide scope and impact

• Develop swarming autonomy algorithms to safely perform a variety of missions across both small and large UxS. • Build and maintain track correlation and multi-target tracking systems that will immediately get real world use.. • Define the inter-robot and C2 communication protocols required to enable tactical swarm decision making on the edge. • Build the core on-vehicle software platform to allow integration of a variety of first and third-party sensors, payloads, and software modules. • Create and validate physically realistic simulations of UxS. • Train, tune, and test automatic target recognition and track management systems using the latest advancements in neural networks. • Perform electronics prototyping including troubleshooting complex mixed hardware-software systems. • Write clean, maintainable, and efficient code. • Travel up to 25% of the time for onsite test and integration events.

• Architect a frontend for a Command & Control (C2) system for heterogeneous aircraft swarms. • Build distributed, collaborative real-time infrastructure for controlling large numbers of aircraft in real-time with intermittent communications. • Develop and test new user interface concepts for swarming UAVs for representing data like vehicle telemetry, sensor data, scheduling, crew resources, data link management and more. • Own key new full stack features from design to deployment. • Ship great software early & often with excellent CICD, QA, DevSecOps.

• Build, ship, and operate backend services in Go for production use cases with real reliability and correctness requirements. • Design systems that process high-volume, event-driven data with clear audit trails and reproducible behavior. • Extend and improve existing platform capabilities without adding unnecessary complexity. • Partner closely with Product and Engineering to turn ambiguous financial-services problems into concrete technical solutions. • Build customer-facing AI features that apply LLMs and ML models to real compliance problems, with attention to evaluation, latency, cost, and failure handling in production. • Help raise engineering quality through strong technical judgment, mentoring, and pragmatic decision-making.