Principal Engineer, Shield AI

• 15+ years of related experience developing large, production quality software systems
• Expertise and deep experience with modern C++ (C++17 and beyond)
• Expertise in deep experience architectural design and implementation of large and complex distributed systems
• Experience with Git and code management tools
• Passionate about developing high-quality and optimized software solutions
• Excellent software hygiene regarding code documentation, unit testing, bug tracking
• Strong technical collaboration skills and a desire to develop new skills
• Excited by a fast-moving environment with a highly motivated group
• Demonstrated record of working hard, being a trustworthy teammate, holding yourself and others to high standards, and being kind to others
• Fluid intelligence that allows one to operate effectively in sometimes ambiguous conditions, while finding opportunities to drive technical efforts and force multiply

Desirable

• The Special Projects team at Shield AI is an elite force within the office of the CTO
• It consists of a group of very senior (L5-L8) and highly experienced software engineering experts from diverse fields (aerospace, robotics, cloud infrastructure, game development, interactive media design, …)
• The charter of this group is to steer technology development towards strategic alignment with the CTO’s vision, through tactical insertion into teams and technologies across the organization
• Individuals within this team make direct and at times forward-sprinting contributions to all three pillars of Hivemind, Shield AI’s software ecosystem for developing and deploying resilient intelligent teaming for aircrafts
• Hivemind consists of three products: Hivemind Edge (autonomy for the edge; a models-based, modular and open architecture C++ codebase), Hivemind Design (Shield AI's AI Factory for the design, development, and testing of Hivemind Edge systems; a service-oriented architecture leveraged through an SDK, CLI, and web portal; a Go, Python, Typescript codebase), and Hivemind Commander (Software and hardware to support rich human-in-the-loop and human-on-the-loop interactions with the Hivemind; a C++-based back-end for interaction with Hivemind Edge, and a web-application UI for mission planning, command and control by operators implemented in a Typescript/React codebase)
• The Special Projects team is chartered to operate effectively within ambiguity. While this team does not own any software products, it tactically and strategically impacts the development of all foundational Hivemind products and leverages those technologies to rapidly deliver low-TRL solutions
• This work happens should-to-shoulder with the product teams in some cases, and in a forward-sprinting manner within the Special Projects team in other cases. The result is direct contribution to products in the former case, and development of reference implementations in the latter
• The Special Projects team also functions as a pipeline for product and solution engineering teams across the organization. Individuals who enter the Special Projects team rapidly gain depth and breadth in their understanding of the Hivemind software ecosystem. This positions them well for leading technology development effort across the product and solution organization
• As part of the Special Projects team, you will work on the integration of Hivemind Edge, Design and Commander into an integrated product
• Technology Strategy Ideation: Create the required technologies for rapid development of architectures to facilitate technology strategy articulation
• Iterate Rapidly with Customer Feedback: Demonstrate developed architectures as solutions to the customer and gather feedback; iterate
• Create Reference Implementations: Create reference implementations for potential future products or product components
• Explore Future Technologies: Explore and evaluate future hardware and software technologies that are relevant to Shield AI’s product roadmap and potentially high-ROI, but beyond the scope of current Direct and IRAD projects in engineering
• Identify areas of technical debt across the stack, analyze and synthesize solutions and paths towards achieving them