8+ years of US Experience - Lead Software Engineer and Architect, Herndon, VA or Hybrid

The role

We are seeking a hands-on software engineering leader to own AIOS software architecture and lead the SWE

team in design, implementation, integration, and testing. Reporting to the Chief Product Officer, you will

operate alongside the Director of Industrial AI and collaborate closely with our Industrial AI Scientist to turn AI

methods and industrial requirements into reliable, maintainable software.

You will organize engineering delivery while personally contributing to critical design, coding, code review, and

debugging. Strong, demonstrated experience using coding agents to deliver real software is essential. You will

establish how the team uses these tools effectively and remain accountable for the quality of the resulting

system.

Responsibilities

Software architecture. Translate agreed requirements into clear modules, data schemas, APIs, and execution

flows. Define interface contracts and maintain compatibility across AIOS components and robot execution

interfaces. Use concise diagrams and specifications to make designs reviewable and implementable. Reuse

proven components and keep complexity proportional to the need.

Research integration. Work with the Industrial AI Scientist and Director to turn algorithms and prototypes into

tested software modules. Agree on inputs, outputs, assumptions, failure behavior, and acceptance criteria;

coordinate changes that affect AI behavior or scientific methods.

Team leadership and delivery. Own cross-location coordination and management of SWE team members. Plan

milestones, assign ownership, manage dependencies, and mentor engineers. Establish clear written handoffs,

practical time-zone overlap, and consistent engineering standards across locations. Lead design and code

reviews, resolve integration problems, and communicate progress, risks, and trade-offs to the Chief Product

Officer.

Coding-agent development. Build repeatable practices for agent-assisted implementation, refactoring, testing,

and documentation. Maintain repository instructions and task context; constrain change scope, review

generated code and tests, and prevent unnecessary rewrites or unsupported assumptions. Coach the team in

these practices.

Testing and release quality. Own automated builds, continuous integration, unit and integration testing, end-to-

end verification, and release readiness. Use representative data and reproducible environments. Distinguish

validation with mocks, recorded data, simulation, and real hardware; resolve interface failures before release.Required qualifications

 Demonstrated ownership of a substantial software system through architecture, implementation, delivery,

and maintenance, with the ability to explain design decisions and operational trade-offs.

 Strong Python software engineering skills and experience designing modular systems, structured data

models, APIs, and reliable interfaces between components.

 Experience leading engineers: planning work, assigning responsibilities, reviewing designs and code,

mentoring team members, and delivering integrated milestones.

 Practical experience integrating AI or ML components into larger software applications, including data

processing, model interfaces, and evaluation workflows.

 Strong debugging and verification skills, including Git, automated testing, continuous integration,

dependency management, and reproducible development environments.

 Ability to clarify ambiguous requirements, communicate through concise diagrams and specifications, and

maintain scope discipline in a small, evolving team.

 Demonstrated coding-agent experience meeting the expectations below.

Coding agent experience

Candidates must be able to show how they have used coding agents to deliver and maintain meaningful changes

in an existing codebase. We value demonstrated engineering outcomes and judgment over a particular tool or

number of years of use.

 Translate requirements into bounded agent tasks with explicit interfaces, constraints, and acceptance

criteria, using relevant repository context.

 Review and debug generated code directly; identify incorrect assumptions, compatibility breaks, excessive

complexity, and unnecessary changes.

 Design verification from requirements and realistic failure cases, and critically review agent-generated tests

rather than relying solely on a passing test suite.

 Explain a concrete delivery example, including what the agent got wrong, how you corrected it, and the

effect on delivery time, defects, or rework. Handle proprietary code and data through approved tools and

access practices.

Preferred experience

 Robotics, industrial automation, computer vision systems, or software that interfaces with physical

equipment.

 Workflow or task execution engines, reusable skill libraries, schema validation, and versioned interfaces.

 Strong C++ development experience. TypeScript experience relevant to system integration is also a plus;

experience collaborating across backend, AI, robotics, and user-interface development.

 Experience in cross-location coordination and management of engineering teams, with clear communication,

coordinated delivery, and effective handoffs across time zones.

 Model-based or diagram-driven software design with explicit contracts and traceable acceptance tests.