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Senior Ai Infrastructure Engineer Jobs in Raleigh, NC

Translate research into usable outcomes for engineering and security teams, including proof-of ... and infrastructure teams to connect research insights with NVIDIA's highest-impact security ...

Translate research into usable outcomes for engineering and security teams, including proof-of ... and infrastructure teams to connect research insights with NVIDIA's highest-impact security ...

Senior AI Technologist

Raleigh, NC · On-site +1

$48.75 - $63/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Senior AI Technologist

Raleigh, NC · On-site

$48.75 - $63/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

... AI infrastructure solutions. This role serves as a technical leader and trusted advisor ... Collaborate with Product Management, Engineering, Marketing, Sales, Strategic Alliances, and ...

Showing results 41-60

Senior Ai Infrastructure Engineer information

See Raleigh, NC salary details

$21.9K

$123.4K

$170.6K

How much do senior ai infrastructure engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for senior ai infrastructure engineer in Raleigh, NC is $123,424.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,500.00 and $143,400.00 per year, depending on experience, location, and employer.

What does a senior AI infrastructure engineer do?

A Senior AI Infrastructure Engineer is responsible for designing, building, and maintaining the large-scale computing systems that support artificial intelligence (AI) and machine learning (ML) workloads. They work on optimizing data pipelines, managing cloud or on-premise infrastructure, ensuring scalability, and enabling efficient training and deployment of AI models. These professionals collaborate closely with data scientists, software engineers, and IT teams to create robust, high-performance environments that support the rapid development and deployment of AI solutions.

What are the key skills and qualifications needed to thrive as a senior AI infrastructure engineer?

To thrive as a Senior AI Infrastructure Engineer, you need deep expertise in computer science, cloud computing, distributed systems, and AI/ML frameworks, often supported by a relevant degree and significant experience. Proficiency with tools such as Kubernetes, Docker, TensorFlow, PyTorch, and cloud platforms like AWS or Azure—as well as experience with CI/CD pipelines—is typically required. Strong problem-solving abilities, collaboration, and effective communication are standout soft skills for this role. These competencies are crucial for designing scalable, reliable AI infrastructure that supports complex machine learning workflows and organizational goals.

What are some typical challenges faced by senior AI infrastructure engineers when scaling AI systems for production?

Senior AI Infrastructure Engineers often encounter challenges related to managing large-scale data pipelines, ensuring low-latency model serving, and maintaining system reliability as user demand grows. Balancing resource allocation for compute-intensive workloads, optimizing infrastructure costs, and implementing robust monitoring are common hurdles. Collaboration with data scientists, DevOps, and product teams is crucial to streamline deployment cycles and rapidly address issues as they arise. Mastery of distributed systems and cloud platforms often distinguishes top performers in this role.

What are the most commonly searched types of Ai Infrastructure Engineer jobs in Raleigh, NC?

The most popular types of Ai Infrastructure Engineer jobs in Raleigh, NC are:

What are popular job titles related to Senior Ai Infrastructure Engineer jobs in Raleigh, NC?

For Senior Ai Infrastructure Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

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The top searched job categories for Senior Ai Infrastructure Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Senior Ai Infrastructure Engineer jobs?

Cities near Raleigh, NC with the most Senior Ai Infrastructure Engineer job openings:

Infographic showing various Senior Ai Infrastructure Engineer job openings in Raleigh, NC as of August 2026, with employment types broken down into 77% Full Time, 20% Part Time, and 3% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $123,424 per year, or $59.3 per hour.

Senior AI Security Researcher

NVIDIA

Durham, NC • On-site

Other

Re-posted 10 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies


Job description

NVIDIA is looking for a Senior AI Security Researcher to help define how frontier AI systems, agentic applications, and AI-enabled security automation are tested, attacked, defended, and safely deployed. You will build new methods, tools, evaluations, and proofs of concept that help NVIDIA understand and reduce security risk across AI models, AI platforms, autonomous agents, cloud services, developer tooling, and accelerated computing systems!

We are looking for a researcher who can move fluidly from open-ended research questions to application within working systems: someone who can discover novel failure modes, build rigorous evaluation harnesses, prototype adversarial and defensive techniques, and turn findings into practical mitigations for engineering teams. The right person may come from AI security, ML security, malware data science, cyber-defense research, adversarial ML, LLM security, offensive security, threat hunting, or applied security research at scale!

What You'll Be Doing:

  • Develop and answer open-ended AI security research questions that helps NVIDIA understand, measure, and reduce risk in frontier models, agentic systems, AI platforms, and AI-enabled products.

  • Develop practical methods, prototypes, evaluations, or tools that reveal how AI systems can fail under adversarial conditions and how those risks can be mitigated.

  • Explore a range of AI security problems, such as LLM and agent security, adversarial testing, model evaluation, cyber-defense automation, vulnerability discovery, secure deployment, or autonomous response.

  • Translate research into usable outcomes for engineering and security teams, including proof-of-concept demonstrations, benchmarks, technical guidance, mitigations, and secure-by-design recommendations.

  • Collaborate across offensive security, product security, AI research, platform, cloud, and infrastructure teams to connect research insights with NVIDIA's highest-impact security priorities.

  • Help shape NVIDIA's AI-security research strategy by mentoring others, identifying emerging risks, and building repeatable practices for evaluating and defending AI systems.

What We Need to See:

  • 12+ years of experience in AI security, cybersecurity research, applied ML research, offensive security, cyber defense, or related technical fields.

  • Demonstrated record of original research and practical impact, such as deployed security ML systems, AI-security evaluations, CVEs, patents, publications, conference talks, open-source tools, production mitigations, or funded research programs.

  • Hands-on ability to build working research systems in Python and modern ML/data tooling such as PyTorch, JAX, TensorFlow, scikit-learn, Pandas, NumPy, Spark, BigQuery, or comparable platforms.

  • Experience with one or more AI-security areas: LLM security, adversarial ML, model evaluation, agent security, prompt injection, model backdoors, data poisoning, model abuse, secure RAG, synthetic data, or AI-enabled security automation.

  • Strong cybersecurity foundation, including threat modeling, adversary simulation, exploit or vulnerability research, malware analysis, network defense, threat hunting, detection engineering, digital forensics, secure code review, or incident-response automation.

  • Ability to work across ambiguous research problems and practical product constraints, translating findings into prioritized recommendations and measurable security outcomes.

  • Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Cybersecurity or a related field.

  • Experience leading AI-security research for major models, AI platforms, security products, or large-scale production systems.

  • A track record of building security ML systems that operate at real-world scale,

Ways to Stand Out from the Crowd:

  • Published work or public technical leadership in AI security, malware data science, adversarial ML, LLM security, cyber-defense automation, or offensive AI.

  • Experience developing benchmarks, challenge datasets, red-team tools, evaluation suites, or simulation environments for AI and security systems.

  • Deep knowledge of attacker tradecraft, including living-off-the-land techniques, supply-chain abuse, application-layer AI attacks, data exfiltration, and abuse of autonomous tooling.

  • Experience with low-level systems security.

  • History of mentoring researchers, winning or leading research programs, filing patents, publishing papers, or speaking at major security and AI venues.

In this role, your research will help NVIDIA build AI systems that are not only powerful, but trustworthy, resilient, and secure. You will work with world-class researchers, engineers, and security teams on problems that matter to NVIDIA's products, customers, and the broader AI ecosystem.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 12, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

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

Year founded

1993