Standard Job Description

Responsible for developing, integrating, and deploying autonomy and artificial intelligence algorithms for mission systems, supporting the technology development life cycle from requirements generation through development, integration, and testing, as well as research in some organizations.  Develops, integrates, and implements algorithms to enable perception, motion/mission planning, controls, etc. functionality in LM products and platforms; Translates requirements and applies requirements to development code, integrating autonomy, AI or machine learning algorithms to LM products and platforms; Determines software methods to best acquire and execute knowledge; Implements algorithms into software to train systems to recognize patterns and perform specific functions; Responsible for various phases of developing and maintaining autonomy software from requirements generation, software design and development to integration, testing, troubleshooting and debugging, and implementation; Review test outcomes, conducts troubleshooting, and works to debug issues; Develops human-machine interface scenarios, breaking missions into tasks; Documents interface requirements and implements human-machine interfaces

Specific to this position:
We are seeking a motivated and experienced engineer with a strong technical background in AI/ML who is eager to apply and grow a Red Teaming mindset. This role is ideal for those who enjoy thinking like the adversary, breaking complex systems to make them stronger, and exploring the boundaries of modern AI technologies.  As part of the Lockheed AI Center (LAIC), this role will enable success across the diverse portfolio of Lockheed Martin AI capabilities in support of our National Defense customers.  This role will provide opportunities to step into a technical leadership role, lead projects, and lead teams of peers in conducting AI red team evaluations.

Responsibilities for this position include:

• Design, plan, and perform Red Team assessments of AI systems, including:
• AI/ML model risks (e.g., adversarial attacks, LLM prompt injection, data/model leakage)
• AI governance and compliance
• Data and supply-chain risk
• Use automated testing tools and develop tactics, techniques, and procedures to evaluate system security, robustness, compliance, and trustworthiness across the AI lifecycle
• Collaborate with AI/ML developers, data scientists, platform engineers, and cybersecurity teams to build robust and secure systems from the ground up
• Help define red teaming methodologies and best practices aligned with standards such as NIST AI RMF and MITRE ATLAS
• Stay current on emerging threats, adversarial techniques, and responsible AI principles

Why Join Us:
This is your chance to help shape the frontier of AI security. We offer:

• The opportunity to learn and grow into a Red Team leader
• Flexible remote work, collaborative team culture, and mentorship
• A mission-driven environment where your work directly protects systems of national importance

If you are an AI engineer who wants to think like a hacker — or a systems hacker ready to dive deep into AI — we want to meet you.

Basic Qualifications

• Bachelor’s or master’s degree in computer science, engineering, security, or a related field
• Proficiency in python, with familiarity in other relevant languages (e.g., C++, C)
• Experience with Linux OS
• Experience in AI/ML model development, testing, or deployment
• U.S. citizenship required

Desired Skills

• Experience in cybersecurity, vulnerability analysis, and risk identification
• Experience in secure data engineering, governance, or compliance in AI workflows
• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn)
• Experience building tools or frameworks for ML validation, testing, or compliance
• Experience engineering LLM-based, agentic, or computer-vision AI solutions
• Knowledge of adversarial ML techniques or ethical AI risks (e.g., fairness, explainability)
• Exposure to MLOps, LLMOps, or secure model deployment practices
• Awareness of AI-specific risks and standards such as MITRE ATLAS and NIST AI RMF
• Experience in adversarial testing, reverse engineering, or system-level red teaming
• Experience with adversarial AI tools like PyRIT, Adversarial Robustness Toolkit, and Garak, or adversarial AI platforms like BlackIce