Shield AI is scaling and growing rapidly. The ideal candidate will demonstrate adaptability, a growth mindset, and a willingness to learn new technologies and methodologies quickly in a fast-paced, evolving environment. This is an opportunity to contribute to something truly remarkable,advancing autonomy that is changing the world,while thriving in a mission-driven, collaborative, and high-performance culture.

Responsibilities:

• Develop automated regression, integration, and system-level tests to ensure Hivemind software quality and stability across releases.
• Identify, reproduce, and diagnose software issues,collaborating closely with development teams to drive fixes and improvements.
• Create and execute test plans and documentation for autonomy software in simulated environments, ensuring mission and safety requirements are met.
• Design, implement, and maintain simulation-based test frameworks to validate Hivemind autonomy behavior and performance.
• Build tools and utilities in Python to automate testing, data processing, and analysis workflows.
• Develop test harnesses and data validation tools for Software-in-the-Loop (SIL) / Hardware-in-the-Loop (HIL) / Vehicle-in-the-Loop (VIL) and simulation environments.
• Contribute to the definition of testing methodologies, metrics, and performance benchmarks for autonomy software validation.
• Support the scaling and reliability of simulation infrastructure used for large-scale software validation.
• Maintain detailed and accurate test documentation, ensuring traceability and knowledge sharing across teams.
• Work with developers to integrate test coverage directly into the development pipeline (CI/CD).

Requirements:

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or related technical field.
• 3–5 years of experience in software integration, testing, or quality assurance, preferably in robotics, aerospace, or autonomous systems.
• Proficiency in Python for test automation, scripting, and data analysis.
• Experience with simulation environments (e.g., Gazebo, Unreal, or custom simulation frameworks) and test automation tools.
• Strong understanding of software testing principles, including integration, regression, and system-level validation.
• Familiarity with continuous integration (CI/CD) and test pipelines (e.g., GitLab CI, Jenkins).
• Excellent analytical, problem-solving, and debugging skills.
• Strong collaboration and communication skills with software and systems teams.
• Adaptability, growth mindset, and willingness to learn new technologies quickly in a fast-paced, scaling environment.
• Self-starter with a sense of urgency, motivation, and comfort operating in ambiguity.
• U.S. Citizenship and ability to obtain and maintain a SECRET clearance.

Preferences:

• Experience testing autonomous systems, robotics software, or flight autonomy algorithms.
• Familiarity with C++ and software/hardware integration concepts.
• Experience with HIL or VIL test environments.
• Exposure to machine learning or AI-driven autonomy systems.
• Background in simulation infrastructure design, distributed testing, or test data management.
• Quality Assurance (QA) experience, including process definition, metrics, and validation tracking.
• Experience with aerospace, defense, or mission-critical software.
• Active SECRET clearance preferred.

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Responsibilities:

System Level Quality Ownership: Own system level quality outcomes for the ART, ensuring the integrated solution is validated end to end. Ensure system level testing validates integration and readiness and does not compensate for missing team level verification. Provide a single point of accountability for ART level quality visibility and decision support.

Scenario Governance & Must Pass Coverage: Own and maintain the ART must pass scenario catalog, ensuring scenarios reflect business intent, deployment scope, and risk. Curate, prioritize, and evolve scenarios based on escaped defects, deployment outcomes, and PI learning. Ensure scenarios are executed consistently and results are recorded as readiness evidence.

System & Regression Test Orchestration: Orchestrate system integration testing, end to end business scenario execution, and ART level regression in integrated environments (primarily QA). Coordinate trigger-based regression execution (build, QA deploy, prerelease), ensuring failures are routed to owning teams for remediation. Ensure regression coverage is layered, risk based, and scalable, not monolithic.

Readiness Evidence & Deployment Support: Own deployment, release, and feature flag readiness reporting, consolidating evidence for Sprint 2 and Sprint 4 deployments. Ensure readiness decisions are based on explicit evidence, including: regression outcomes, must pass scenario execution, feature flag ON/OFF validation, documented risks and waivers. Support GO / GO with risk / NO GO decision forums with clear quality signals.

Defect Triage & Risk Visibility: Coordinate system level defect triage, ensuring ownership, prioritization, and visibility of cross-team issues. Track and surface systemic quality risks and integration issues to ART leadership. Ensure explicit risk acceptance is documented when defects or gaps are waived.

Environment & Test Data Oversight: Track QA and UA environment stability and test data readiness as ART level risks or impediments. Reinforce correct environment usage: QA as the primary integrated environment for functional confidence, UA for selective business validation, UA1, Batlab, and Production for deploy/ops verification only. Partner with DevOps and teams to resolve environment and data issues impacting system validation.

Continuous Improvement & Inspect & Adapt: Consolidate quality inputs for Inspect & Adapt, including escaped defects, regression effectiveness, scenario coverage gaps, and environment issues. Drive ART level quality improvements with named owners and funded capacity each PI. Ensure learning results in measurable, planned change rather than ad hoc fixes.

Collaboration & Enablement: Partner closely with: System Automation Tester on suite health, automation standards, and expansion, Product Management and Business Owners on outcome validation and risk acceptance, RTE on quality visibility, capacity funding, and escalation of systemic risks, Provide guidance and coaching on system level quality expectations and evidence standards.

Success Measures: Deployment and release decisions are supported by clear, trusted readiness evidence. Must pass scenarios accurately reflect business critical flows and are consistently executed. System level defects and risks are visible early and owned by the correct teams. Quality improvement actions are planned, funded, and completed each PI.

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What you'll do

Plan, conduct and moderate workshops to define integration architecture and interface requirements.

• Configure and integrate SAP PP-PI and QM with other SAP modules (e.g., MM, SD, EWM) and external systems.

• Support process design, harmonization and optimization within the P2M domain.

• Define test data and coordinate unit, integration, and user acceptance testing in close collaboration with functional peers and subject matter experts.

• Identify and realize opportunities for process improvements and system optimization.

• Develop and maintain high-quality documentation for configurations, processes and interfaces.

• Manage and guide offshore teams and/or 3rd party AMS providers, ensuring delivery quality and alignment.

• Collaborate with global business stakeholders to understand requirements and translate them into sustainable SAP solutions.

• Communicate effectively across all levels of the organization, ensuring clear alignment between business and IT, often across geographies and remote teams.

What you need

What you need

Intro.

• Required skill 1

• Required skill 2

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