Senior Engineer, Human Machine Teaming - Development (R5651)

The Human Machine Teaming (HMT) Group within Hivemind Solutions’ Strategic Product Development department at Shield AI is hiring an Engineer II or Senior Engineer to build out our developer experience and development capabilities. At Shield AI, HMT refers to the design, development, management, and assurance of the adaptive relationships between end users and the systems they operate—not just an interface problem, or a function-allocation exercise. As part of the HMT group, this role will work with SDK and HMI development teams and product managers across Shield AI to enable effective product design, and to ensure the end product will satisfy customer and market needs before its developed. 

Working alongside the HMT Design, Experimentation, and Operations Leads, you will interact with developers as a user population. You will elicit how they build, evaluate, and deploy autonomy using SDK tools such as Forge and Commander, and characterize the requirements their tooling has to meet. You are the conduit between the engineers who build development tools and HMIs, the HMT capabilities that define what effective teaming requires, and the customers whose operational needs we serve. 

If you have developed software yourself and would rather raise the HMT quality of everything the organization ships than own a single service, this is your opportunity to make a lasting impact. 

Become a skilled user of the Hivemind SDK and its autonomy modules, building with the same tools the development teams and our customers do. 

Conduct knowledge elicitation and applied human factors and front-end analysis with developers as users of the Hivemind SDK, tools such as Forge and Commander, and with other HMIs. 

Translate developer, operator, and customer needs into design and development requirements that SDK and HMI teams can implement and test. 

Specify HMT requirements for developer-facing and operator-facing interfaces, and review proposed designs against them. 

Assess whether delivered tools, code, and systems satisfy the stated user and HMT requirements, and document gaps with recommended remedies. 

Define acceptance criteria and evaluation methods for HMT requirements, and maintain traceability from developer and operational need through requirement, acceptance and robustness testing. 

Develop and maintain HMT design and development guidance, documentation, and training materials that developers can apply without you in the room. 

Represent HMT in design reviews, architecture decisions, and trade-off discussions, making the HMT case in engineering terms. 

Convert recurring friction in the development toolchain and the HMIs it produces from one-off complaints into durable, prioritized requirements. 

Roll up your sleeves and work alongside the development team as needed, implementing requirements in the code yourself, and working through integration and API issues alongside them, so that effective HMT is built into the user experience from the outset. 

Feed implementation constraints and technical realities back into HMT design and experimentation, so that requirements stay buildable. 

Support field events and operator engagements, and carry what you learn there into requirements for the development teams. 

Travel to company, test, demonstration, and customer locations to conduct project work (approximately 40%). 

Experience in an applications, integration, or solutions engineering role, working between customers and product engineering. 

Experience with autonomy, robotics, or simulation software, and with build, simulation, and test toolchains. 

Hands-on experience with human machine teaming, MUM-T, human-robot interaction, or applied artificial intelligence, specifically in mission autonomy applications such as UAV Groups 3–5. 

Experience with mission planning, C2, and battle management concepts, processes, and doctrine, and with ground control stations or HMIs. 

Experience with developer-experience research, developer productivity measurement, or qualitative study of how engineering work gets done. 

Familiarity with developer platforms and workflows, such as Git, GitLab, CI/CD, or cloud-native development practices. 

Familiarity with traceability methods, or with AI assurance frameworks. 

Willingness to use agentic AI to speed the path from design concept to fielded product.