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Cybersecurity Scenario Designer Jobs in Missouri

The Digital Identity Manager (Entra ID) is responsible for designing, implementing, and supporting ... Preferred Certifications -SC 300 (Identity and Access Administrator) -SC 100 (Cybersecurity ...

The Digital Identity Manager (Entra ID) is responsible for designing, implementing, and supporting ... Preferred Certifications -SC 300 (Identity and Access Administrator) -SC 100 (Cybersecurity ...

Cybersecurity Scenario Designer information

What is a cybersecurity scenario designer?

Cybersecurity Scenario Designers are professionals who create realistic simulations and scenarios to test and improve an organization's cybersecurity defenses. They develop exercises such as cyberattack simulations, tabletop exercises, and red team/blue team drills to help security teams prepare for real-world threats. Their work involves understanding potential cyber threats, designing scenarios that mimic these threats, and evaluating how well security teams respond. This role is crucial for identifying vulnerabilities and enhancing an organization’s ability to detect, respond to, and recover from cyber incidents.

What are some common challenges faced by cybersecurity scenario designers when creating realistic training simulations?

Cybersecurity Scenario Designers often face the challenge of balancing realism with training objectives—scenarios must be complex enough to reflect evolving threats, but not so intricate that they overwhelm participants. Keeping scenarios up-to-date with the latest attack vectors and techniques requires continual research and collaboration with incident response teams. Additionally, designers must work closely with technical experts and trainers to ensure that scenarios are relevant to the organization's environment and that learning outcomes are measurable and actionable.

What are the key skills and qualifications needed to thrive as a cybersecurity scenario designer, and why are they important?

To thrive as a Cybersecurity Scenario Designer, you need a strong understanding of cybersecurity principles, threat modeling, and incident response, often supported by a degree in computer science or a related field. Familiarity with tools such as SIEM platforms, penetration testing suites, and cyber range environments, along with certifications like CISSP or CEH, is typically required. Creativity, attention to detail, and effective communication are crucial soft skills for crafting realistic scenarios and collaborating with cross-functional teams. These skills and qualifications ensure the development of relevant, challenging scenarios that prepare organizations to defend against evolving cyber threats.

What are popular job titles related to Cybersecurity Scenario Designer jobs in Missouri?

For Cybersecurity Scenario Designer jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Cybersecurity Scenario Designer jobs in Missouri look for?

The top searched job categories for Cybersecurity Scenario Designer jobs in Missouri are:

What cities in Missouri are hiring for Cybersecurity Scenario Designer jobs?

Cities in Missouri with the most Cybersecurity Scenario Designer job openings:

Infographic showing various Cybersecurity Scenario Designer job openings in Missouri as of July 2026, with employment types broken down into 89% Full Time, 7% Part Time, and 4% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.

Senior Applied AI Engineer, Cybersecurity

NVIDIA Gruppe

California, MO • On-site

$184 - $357/hr

Other

This job post has expired 2 days ago. Applications are no longer accepted.


Key responsibilities

  • Partner with security practitioners to identify high-impact workflows and lead the delivery of agentic systems that improve analyst decision-making and accelerate detection, investigation, and response.

  • Build and develop context-aware agents that analyze security data streams and organizational knowledge, use approved tools, and support greater autonomy.

  • Take AI capabilities from experimentation to production using software engineering and MLOps/LLMOps practices, including building evaluation, observability, versioning, deployment, and rollback processes.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

The Cyber Defense Applied AI team is building NVIDIA’s agent-first security operations. We develop and operationalize trusted AI agents that augment analyst judgment, automate security work, and improve the efficiency of detection, investigation, and response processes. We combine NVIDIA AI technologies with open models, frontier models, and strategic partner capabilities to apply the best approach to each security problem.

As a Senior Applied AI Engineer, Cybersecurity, you will build AI systems that perform real security work. You will develop agents that reason over security telemetry and organizational context, use security tools, and support investigation and response. You will take capabilities from experimentation through evaluation, optimization, deployment, and production operation. You will also assess emerging approaches, adapt what already works, and build new solutions where meaningful gaps remain. This role carries significant technical autonomy and influence. You will make evidence-based decisions about what to build, adopt, integrate, or develop with partners and use operational results to shape the Applied AI roadmap!

What you will be doing:
  • Partner with security practitioners to identify high-impact workflows and lead the delivery of agentic systems that improve analyst decision-making and accelerate detection, investigation, and response.
  • Provide technical direction for complex agentic AI initiatives, shaping architecture, project goals, and engineering decisions across teams. Drive work from ambiguous problems to measurable operational outcomes.
  • Build and develop context-aware agents that analyze security data streams and institutional knowledge, use approved tools, and support greater autonomy as operational evidence and controls allow.
  • Establish repeatable evaluation for models and agents using realistic security environments, curated datasets, analyst ground truth, and task-specific benchmarks. Evaluate end-to-end behavior through automated scoring, trajectory analysis, and adversarial testing.
  • Use evaluation results, production traces, and analyst feedback to improve agent quality, reliability, and efficiency. Optimize models, retrieval, context, orchestration, and inference against measurable security outcomes.
  • Take AI capabilities from experimentation to production using strong software engineering and MLOps/LLMOps practices. Build continuous evaluation, observability, versioning, controlled deployment, and safe rollback into the lifecycle.
  • Evaluate NVIDIA AI technologies alongside open-source, frontier, and strategic partner capabilities within an interoperable, multi-model approach. Make evidence-based recommendations on what to adopt, adapt, build, integrate, or co-develop.
  • Translate technical findings into clear recommendations that influence architecture, Applied AI priorities, and partner roadmaps. Turn proven approaches into reusable capabilities that strengthen NVIDIA and the broader open, interoperable AI security ecosystem.
What we need to see:
  • BS, MS, or PhD in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Cybersecurity, or a related technical field, or equivalent experience.
  • 8+ years of relevant experience building and shipping AI, machine learning, or intelligent software systems, including technical ownership of complex production initiatives.
  • Strong software engineering skills, particularly in Python, with experience building production systems using languages such as TypeScript or C#. Demonstrated ability to design reliable and scalable systems beyond prototypes or experimental notebooks.
  • Hands-on experience designing and developing modern AI systems using large language models, retrieval-augmented generation, agentic architectures, agent harnesses, or related approaches.
  • Experience designing AI evaluations and benchmarks using curated datasets, ground truth, task-specific metrics, automated evaluators, error analysis, and expert feedback.
  • Experience taking AI capabilities through experimentation, deployment, monitoring, optimization, and continuous improvement using modern MLOps or LLMOps practices.
  • Demonstrated technical leadership across complex, cross-functional projects. Ability to exercise independent judgment, influence architecture and technical direction, and drive ambiguous problems to measurable outcomes.
  • Strong understanding of cybersecurity or experience applying AI and software engineering to security operations, detection, incident response, threat research, or another adversarial domain.
Ways to stand out from the crowd:
  • Deep experience designing evaluation environments and benchmarks for agentic systems, including trajectory-level evaluation, task verifiers, adversarial scenarios, and safety or reliability testing.
  • Experience designing and calibrating LLM-as-a-Judge or other model-based evaluators against human labels, deterministic checks, or task-specific ground truth.
  • Experience developing or optimizing agentic architectures, agent harnesses, orchestration systems, retrieval and context pipelines, or multi-agent approaches for cybersecurity or other complex operational use cases.
  • Familiarity with NVIDIA AI technologies relevant to agent development, evaluation, and deployment, such as NeMo Evaluator, NeMo Gym, NeMo Agent Toolkit, NVIDIA NIM, Triton Inference Server, RAPIDS, or CUDA.
  • Demonstrated technical influence through open-source contributions, benchmarks, publications, patents, conference presentations, or other recognized contributions to AI or cybersecurity.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 22, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US