Autonomous Systems Engineer

What matters most

• Evaluate autonomy against sponsor requirements

  The posting calls for evaluating and improving AI/autonomy performance, identifying capability gaps, and guiding sponsors toward solutions that meet their requirements.

• Execute applied autonomy research

  The role requires experience carrying out autonomy-focused research initiatives and hands-on work in at least one technical area such as perception, learning, control, human–machine teaming, or multi-robot systems.

• Support safe adoption in high-consequence settings

  The engineer will help execute strategy for autonomy applications where assurance, test and evaluation, and societal implications matter.

• Translate advances into useful capabilities

  The role involves tracking robotics advances, working across robotics hardware and cloud computing, building capability in a growth area, and explaining technical issues to expert and nonexpert audiences.

Likely challenges to think through

• Performance versus real-world constraints

  Preparation hypothesis: An approach that performs well in research may be harder to use on physical or constrained platforms. Prepare to explain how you would test performance, identify limitations, and decide what to improve before recommending it.

• Innovation versus assurance

  Preparation hypothesis: Rapidly advancing AI capabilities may be difficult to evaluate confidently in high-consequence applications. Prepare to discuss how test evidence, known failure modes, and societal implications would shape a recommendation without overstating certainty.

• Breadth versus defensible depth

  Preparation hypothesis: The range of technical topics and growth areas may require learning beyond one specialty while still giving sponsors sound guidance. Prepare one concrete research example in depth, then explain how you would assess an unfamiliar domain and communicate its capability gaps.

Topics to prepare

• Autonomy capability gaps

  Review how perception, reasoning, behaviors and collaboration can fail under real-world constraints. As a preparation exercise, map one failure in each area to a possible capability gap. The posting explicitly asks for the ability to explain these challenges.

• Autonomy evaluation and assurance

  Compare ways to judge system performance, test limitations and communicate uncertainty. As a preparation exercise, sketch an evaluation plan for a high-consequence autonomy system, including what evidence would and would not support deployment. Evaluation, test and assurance are stated responsibilities.

• Research advances and sponsor requirements

  Review one recent autonomy or robotics advance and identify its assumptions, limitations and potential fit against a hypothetical sponsor requirement. Tracking advances and advising sponsors against their requirements are stated responsibilities; the hypothetical comparison is a preparation suggestion.

• Robotics and computing tradeoffs

  Compare the constraints of running autonomy on robotics hardware versus in a cloud-based environment. As a preparation exercise, explain how compute availability and physical-system constraints could change an evaluation. Both environments appear in the responsibilities; edge and compute-size-weight-power platforms are preferred, not basic, qualifications.

Skills to revise

• ROS 2 and Docker familiarity

  Practice explaining the purpose of each tool, then run a small ROS 2 example in a Docker environment and note any setup or integration issues. The posting explicitly requests familiarity with both tools, not expertise in a specified workflow.

• Hands-on work in one technical area

  Choose one area named in the basic qualifications—such as computer vision, control theory or multi-robot systems—and revisit a small implementation or experiment. Be ready to explain its inputs, results and failure cases. Hands-on experience is required in at least one listed area, not all of them.

• Autonomy research execution

  Practice framing a testable autonomy question, defining a comparison and recording results and limitations. This exercise prepares for the stated requirement to execute autonomy-focused research initiatives without assuming a particular employer methodology.

• Audience-specific technical explanation

  Give two short explanations of the same autonomy performance gap: one for a technical peer and one for a nonexpert sponsor. The posting explicitly calls for clear written and verbal communication with both audiences.

• Map your evidence to the qualifications

  The posting requires hands-on work in at least one listed autonomy area and experience executing autonomy-focused research. Prepare a one-page map of specific work you can discuss, your contribution, results, and any gaps you would describe candidly.

• Build a project walkthrough

  Prepare a concise account of an autonomy project: the problem, your technical decisions, experiments, performance results, real-world constraints, and what you would improve. Include ROS 2 or Docker only where you have used them; the posting calls for familiarity with both.

• Practice a system design exercise

  As preparation, sketch an embodied-AI system using robotics hardware and, where useful, cloud computing. Explain perception, reasoning, behaviors, interfaces, failure modes, and how constraints would change the design; this is a practice exercise, not a stated interview format.

• Draft an evaluation plan

  The role evaluates solutions against sponsor requirements and addresses assurance, test and evaluation, and societal implications. Prepare a sample plan with measurable criteria, test conditions, capability gaps, and a recommendation that acknowledges uncertainty.

• Prepare a research-to-application example

  The role tracks autonomy advances and builds capability in growth areas such as maritime autonomy, healthcare robotics, or space robotics. Choose one relevant advance and prepare a short explanation of its potential use, evidence still needed, and limitations.

• Rehearse two explanations of the same challenge

  The posting calls for communication with expert and nonexpert audiences. Prepare a technical explanation and a plain-language version of an autonomy challenge, such as a perception failure or human–machine coordination gap.

• Write targeted employer questions

  Bring questions about sponsor requirements, how hardware and cloud work are divided, and how autonomy performance and assurance are evaluated. If relevant, clarify the onsite arrangement and clearance timeline: the posting specifies at least three onsite days weekly and a Secret clearance within one year of hire, with none required initially.