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Llm In Cybersecurity Jobs in Remote, OR (NOW HIRING)

Atos

Apps AI Solution Architect AMS

OR · Remote

$59 - $77.75/hr

European number one in cybersecurity, cloud and high performance computing, Atos Group is committed ... Hands-on exposure to LLM-based ITSM agents and RAG (Retrieval-Augmented Generation) frameworks.

Atos

Apps AI Solution Architect AMS

OR · On-site +1

$59 - $77.75/hr

European number one in cybersecurity, cloud and high performance computing, Atos Group is committed ... Hands-on exposure to LLM-based ITSM agents and RAG (Retrieval-Augmented Generation) frameworks.

All JobsLlm In Cybersecurity JobsLlm In Cybersecurity Jobs in Remote, OR

Llm In Cybersecurity information

See Remote, OR salary details

$56.9K

$132.8K

$185.8K

How much do llm in cybersecurity jobs pay per year?

As of Jun 30, 2026, the average yearly pay for llm in cybersecurity in Remote, OR is $132,831.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,900.00 and $149,900.00 per year, depending on experience, location, and employer.

Which LLM is best for cyber security?

For a cybersecurity professional, large language models like OpenAI's GPT-4 and Google's Bard are widely used due to their advanced natural language understanding and ability to assist with threat analysis, incident response, and security automation. Selecting an LLM depends on the specific use case, data privacy requirements, and integration capabilities, often complemented by cybersecurity tools and certifications. Familiarity with AI ethics and secure deployment practices is also essential in this field.

What jobs can you do with LLM?

With expertise in large language models (LLMs) in cybersecurity, you can pursue roles such as cybersecurity analyst, threat intelligence analyst, security engineer, or AI security specialist. These positions often require skills in machine learning, data analysis, and knowledge of security protocols to develop, implement, and monitor AI-driven security solutions.

What are the key skills and qualifications needed to thrive as an LLM in Cybersecurity, and why are they important?

To excel as an LLM in Cybersecurity, you need a solid legal education (LLB or JD), expertise in cybersecurity law, and an understanding of digital privacy regulations. Familiarity with legal research databases, cybersecurity frameworks (such as NIST or ISO), and certifications like CIPP/US or CISSP can be highly beneficial. Strong analytical thinking, attention to detail, and effective communication skills set candidates apart in this specialized field. These competencies are critical for interpreting complex legal and technical issues, advising organizations on compliance, and mitigating risks in the rapidly evolving cybersecurity landscape.

What is the use of LLM in cyber security?

In cybersecurity, large language models (LLMs) are used to analyze and detect threats by processing vast amounts of textual data, such as logs and alerts. Cybersecurity professionals leverage LLMs for tasks like threat intelligence, automated incident response, and identifying vulnerabilities, often integrating them with security tools and frameworks to enhance defense strategies.

How does an LLM in Cybersecurity contribute to collaboration between legal and technical teams within organizations?

An LLM in Cybersecurity equips professionals with both legal expertise and a strong understanding of cybersecurity principles, enabling them to act as a bridge between legal and technical teams. Individuals in this role often translate complex legal requirements into actionable security policies or help IT teams understand compliance obligations. This collaboration is vital for ensuring that security strategies align with regulatory standards and that organizations are protected from both legal and cyber risks. As regulations and technologies evolve, professionals with an LLM in Cybersecurity are well-positioned to facilitate communication and foster a culture of compliance and security.

What is an LLM in Cybersecurity?

An LLM in Cybersecurity is a Master of Laws degree focused on the legal, regulatory, and policy aspects of cybersecurity and information privacy. This postgraduate program is designed for lawyers and legal professionals who want to specialize in areas such as cybercrime, data protection, and technology law. Students typically study topics like digital evidence, cyber risk management, and international cybersecurity law. The degree prepares graduates for roles in law firms, government agencies, and corporate legal departments dealing with cybersecurity issues.

What is the difference between Llm In Cybersecurity vs Cybersecurity Analyst?

AspectLlm In CybersecurityCybersecurity Analyst
Required CredentialsLegal degree, cybersecurity certifications (e.g., CISSP, CEH)Security certifications (e.g., CompTIA Security+, CISSP), relevant experience
Work EnvironmentLegal and cybersecurity teams, policy development, complianceSecurity operations centers, incident response, threat analysis
Employer & Industry UsageLaw firms, corporate legal departments, cybersecurity firmsBusinesses, government agencies, IT firms

While Llm In Cybersecurity combines legal expertise with cybersecurity knowledge, Cybersecurity Analysts focus on protecting systems and responding to threats. Both roles require cybersecurity certifications, but Llm In Cybersecurity emphasizes legal and compliance aspects, whereas Cybersecurity Analysts concentrate on technical security measures.

Can you make $500,000 a year in cyber security?

Llm in cybersecurity professionals with extensive experience, advanced skills, and certifications such as CISSP or CISA can potentially earn salaries approaching or exceeding $500,000 annually, especially in senior or executive roles like Chief Information Security Officer. However, such high salaries are typically reserved for top-tier experts in large organizations or consulting firms and are not common for entry- or mid-level positions.
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Infographic showing various Llm In Cybersecurity job openings in Remote, OR as of June 2026, with employment types broken down into 1% Locum Tenens, 7% Full Time, 71% Part Time, 20% Contract, and 1% Nights. Highlights an 74% Physical, 4% Hybrid, and 22% Remote job distribution, with an average salary of $132,831 per year, or $63.9 per hour.

Apps AI Solution Architect AMS

Atos

OR • Remote

$59 - $77.75/hr

Other

Posted 7 days ago

Job description

About Atos Group

Atos Group is a global leader in digital transformation with c. 63,000 employees and annual revenue of c. 8 billion, operating in 61 countries under two brands - Atos for services and Eviden for products. European number one in cybersecurity, cloud and high performance computing, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is the brand under which Atos SE (Societas Europaea) operates. Atos SE is listed on Euronext Paris.

The purpose of Atos Group is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

Apps AI Architect 539988

Location: North America (Remote)

Role Summary

The Apps AI Architect will play a pivotal role in transforming how we design, build, and manage enterprise applications in the GenAI era. This role blends deep application architecture expertise - spanning UI/UX, front-end, back-end, integration, data, and cloud - with hands-on AI engineering skills to infuse Artificial Intelligence (including Generative and Agentic AI) across the full application lifecycle - from design and development to modernization and ongoing operations. The Architect will drive innovation, develop reusable AI patterns, and deliver proof-of-value (PoV) initiatives that convert emerging technology possibilities into tangible business impact.

Key Responsibilities

  • Architect AI-Native Applications: Design and implement architectures that integrate AI models (LLMs, predictive, and agentic systems) into application workflows to enable reasoning, automation, and contextual decision-making.
  • End-to-End Application Design: Lead the design of UI/UX flows, user-facing AI interactions, conversational interfaces, and AI-augmented user journeys across web and mobile applications.
  • Drive Modernization Through AI: Reimagine legacy and digital applications by embedding AI capabilities that enable modernization, optimization, and transformation across app portfolios. Design modernization frameworks leveraging AI for architecture discovery, business-rules extraction, and application rationalization. Embed intelligence in re-platformed or refactored applications to create truly AI-native modernization.
  • Legacy-to-Modern Mapping: Architect solutions that transform legacy applications into modern Java, .NET, microservices, or cloud-native platforms while preserving core business rules and logic.
  • Infuse AI Across Dev & Ops: Partner with delivery and support teams to embed AI in software engineering, testing, incident management, and observability - driving efficiency, resilience, and proactive operations.
  • Tooling & Frameworks: Evaluate, integrate, and optimize AI-assisted tools (e.g., code translators, test generators, documentation bots) within modernization pipelines to accelerate delivery.
  • Integration & Ecosystem: Define strategies to integrate modernized applications into enterprise ecosystems, including APIs, event-driven architectures, and cloud environments.
  • Lead Proofs of Value (PoVs): Design and execute AI-centric PoVs to validate new technologies, tools, and architectures for clients.
  • Collaborate & Evangelize: Partner with pre-sales, delivery, and client stakeholders to identify AI opportunities, shape proposals, and articulate the business value of AI-native transformation.
  • Develop Reusable Assets: Create frameworks, accelerators, and reference architectures to scale adoption of GenAI and LLM-enabled solutions across multiple accounts.

Required Skills & Experience

  • 10-15 years of experience in Application Architecture, Engineering, or Digital Transformation, with at least 2-3 years in AI/ML or GenAI implementation.
  • Strong experience with Azure OpenAI, OpenAI APIs, Vertex AI, AWS Bedrock, LangChain, LlamaIndex, or similar LLM platforms.
  • Deep understanding of modern UI/UX architecture, responsive front-end design, and frameworks such as React, Angular, Vue, or equivalent.
  • Proficiency in Python, Node.js, or Java, with exposure to LLM integration, prompt engineering, and API orchestration.
  • Experience with leading AI-assisted productivity tools such as Claude, Gemini Code Assist, and GitHub Copilot.
  • Familiarity with observability and AIOps platforms including DataDog, Dynatrace, Moogsoft, Splunk AIOps, and ServiceNow AIOps.
  • Hands-on exposure to LLM-based ITSM agents and RAG (Retrieval-Augmented Generation) frameworks.
  • Experience with MLOps/GenAIOps for continuous model improvement within modernization initiatives.
  • Strong background in application modernization (re-platforming, containerization, microservices, and cloud-native design).
  • Solid understanding of legacy technologies such as Mainframe, Java, and .NET.
  • Knowledge of PromptOps, model observability, AI lifecycle management, and related operational frameworks.
  • Excellent communication, stakeholder management, and customer-facing engagement skills.

Preferred Qualifications

  • Certifications in AI Engineering (Azure, AWS, or Google) or equivalent credentials.
  • Prior experience working in Application Services, AMS, or ADM environments.
  • Exposure to agentic workflows, AI observability, or RAG (retrieval-augmented generation) frameworks.
  • The role requires active engagement across the full lifecycle - from pre-sales solution shaping through design, development, implementation, and ongoing evolution of AI-native applications.
  • Given the evolving nature of AI-native architectures, we welcome candidates who may not meet every requirement but demonstrate strong foundational skills and the ability to grow into the role.

Why This Role Matters

This role is central to our AI-Native Application Services transformation. The Apps AI Architect will directly shape how enterprise applications evolve - blending the power of AI, data, and cloud to create intelligent, adaptive, and self-improving systems that redefine how our clients build, run, and scale their businesses.

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