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Llm Jobs (NOW HIRING)

LLM Specialist

Mclean, VA · On-site

$16.50 - $21.75/hr

The LLM Specialist serves as PenFed's subject matter expert for Large Language Models (LLMs), Generative AI technologies, and emerging foundation models. This role is responsible for evaluating ...

New

LLM Applications Engineer

New York, NY · On-site

$130K - $175K/yr

As an LLM Applications Engineer, you will be the architect of our LLM infrastructure. You won't just be building interfaces; you will be designing the retrieval systems, agentic workflows, and data ...

We are specifically seeking an expert in high-performance LLM serving systems and inference optimization. In this role, you will push the boundaries of how large language models are served. What You ...

We are specifically seeking an expert in high-performance LLM serving systems and inference optimization. In this role, you will push the boundaries of how large language models are served. What You ...

Java AI/LLM

Glen Lyn, VA · Remote

$52.25 - $67.50/hr

AI/LLM skill with * AI/LLM - hugging face model, OLAMA, LLAMA, Mistral * Agentic AI, Open AI, Gemini * Fine tuning of LLM * Lang chain, Lang flow, FAISS, vector database, Cosine similarity search.

We're building the world's first healthcare‑only, safety‑focused LLM - a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation. Work with the ...

LLM Solutions Architect

Concord, NC · On-site

$85K - $120K/yr

ABOUT YOU We are looking for an LLM Solutions Architect who is a builder at heart -- someone who shapes strategy and ships real systems -- to join our Monetization Products team. The best candidate ...

C. is seeking a highly skilled AI/LLM Engineer to design and build intelligent agent-based systems. The role requires strong Python engineering expertise and hands-on experience with modern agent ...

C. is looking for a highly skilled AI/LLM Engineer to design and build intelligent agent-based systems. The role involves developing advanced AI capabilities and ensuring the integration of AI ...

About the Role EnCharge AI is seeking an LLM Inference Deployment Engineer to optimize, deploy, and scale large language models (LLMs) for high-performance inference on its energy efficient AI ...

LLM Infrastructure Engineer

Houston, TX · On-site

$97K - $127K/yr

We are looking for a Senior Python / AI API Engineer to build and deploy production-grade services powering Large Language Model (LLM) applications. This role focuses on developing high-performance ...

AI/LLM Eng 12+ Months New jersey Must have experience in: Large Language Models (OpenAI/Azure OpenAI or similar) Very strong Prompt engineering skilla, function calling, RAG architectures Agentic AI ...

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Llm information

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$85K

$142.7K

$182K

How much do llm jobs pay per year?

As of Aug 4, 2026, the average yearly pay for llm in the United States is $142,663.00, according to ZipRecruiter salary data. Most workers in this role earn between $126,000.00 and $157,500.00 per year, depending on experience, location, and employer.

What jobs can you do with a large language model?

A large language model (LLM) can be used in roles such as AI content developer, chatbot designer, data annotator, or AI researcher. These jobs often require skills in programming, natural language processing, and machine learning tools, and may involve tasks like training, fine-tuning, or deploying language models in various applications.

What are the key skills and qualifications needed to thrive as an LL.M. graduate?

To thrive as an LLM graduate, you need advanced knowledge of legal principles, strong research and analytical skills, and a prior law degree such as an LLB or JD. Familiarity with legal databases, research tools like Westlaw or LexisNexis, and sometimes bar admission or certification in specific jurisdictions is advantageous. Exceptional written and verbal communication, attention to detail, and cross-cultural competence are standout soft skills in this field. These abilities are crucial for interpreting complex legal issues, advising clients, and succeeding in global or specialized legal practice.

What is an LLM?

LLMs, or Large Language Models, are advanced artificial intelligence systems designed to understand and generate human-like text based on vast amounts of data. These models, such as OpenAI's GPT series, are trained on diverse datasets and can perform a range of tasks, including answering questions, writing content, translating languages, and more. LLMs work by predicting the next word in a sequence, allowing them to create coherent and contextually relevant responses. They are widely used in applications like chatbots, virtual assistants, and automated content generation.

What is the difference between Llm vs Paralegal?

AspectLlmParalegal
Required CredentialsLaw degree (JD or equivalent), possibly an LLM for specializationAssociate's degree or certificate in paralegal studies
Work EnvironmentLaw firms, corporate legal departments, academiaLaw firms, corporate legal departments, government agencies
Industry UsageLegal practice, academia, researchLegal support, case preparation, client communication

The main difference is that an Llm is an advanced law degree for specialization or academic purposes, while a paralegal provides legal support and case assistance without being licensed to practice law. Both roles work closely within legal environments, but the Llm is more focused on legal expertise and research, whereas paralegals handle administrative and preparatory tasks.

Which large language model is most in demand?

The most in-demand large language models for jobs like LLM development and deployment are OpenAI's GPT-4 and GPT-3, as well as Google's PaLM and Meta's LLaMA. Skills in fine-tuning, prompt engineering, and understanding these models are highly sought after in the AI industry.

What are some common challenges faced by professionals working with large language models and how can they be addressed?

Professionals working with large language models often encounter challenges such as managing computational resource demands, ensuring data privacy, and mitigating biases in model outputs. Collaboration with data engineers and IT teams is essential to optimize infrastructure and streamline model deployment. Staying updated on best practices and regulatory guidelines helps address ethical concerns and improve model performance. Continuous monitoring and iteration are key to maintaining accuracy and relevance in real-world applications.
What cities are hiring for Llm jobs? Cities with the most Llm job openings:
What are the most commonly searched types of Llm jobs? The most popular types of Llm jobs are:
What states have the most Llm jobs? States with the most job openings for Llm jobs include:
Infographic showing various Llm job openings in the United States as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $142,663 per year, or $68.6 per hour.

$16.50 - $21.75/hr

Full-time

Posted 2 days ago

New


PenFed Credit Union rating

7.6

Company rating: 7.6 out of 10

Based on 14 frontline employees who took The Breakroom Quiz


Job description

Overview

PenFed is hiring a (Hybrid) LLM Specialist at our Tysons, Virginia location. The LLM Specialist serves as PenFed’s subject matter expert for Large Language Models (LLMs), Generative AI technologies, and emerging foundation models. This role is responsible for evaluating, selecting, implementing, securing, and optimizing LLM solutions that support business objectives, enhancing member experiences, improving operational efficiency, and drive employee productivity. The incumbent partners closely with business leaders, Technology, Information Security, Risk Management, Compliance, Data, and AI Engineering teams to translate business requirements into effective AI solutions. The LLM Specialist evaluates technical, security, performance, and cost considerations across AI models and platforms while ensuring LLM deployments align with enterprise AI management, responsible AI principles, privacy requirements, and regulatory expectations. This role serves as a trusted advisor on LLM technologies, helping the organization understand model capabilities, limitations, risks, and opportunities while supporting the successful adoption of Generative AI across the enterprise.


Responsibilities

Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. This is not intended to be an all-inclusive list of job duties, and the position will perform other duties as assigned.

LLM Evaluation & Model Selection

  • Evaluate and recommend Large Language Models (LLMs), foundation models, and Generative AI platforms based on business requirements, technical capabilities, security requirements, and operational considerations.
  • Assess models across criteria including accuracy, latency, context window, performance, scalability, explainability, integration requirements, and business fit.
  • Analyze and communicate technical tradeoffs among commercial, open source, hosted, and enterprise AI solutions.
  • Provide recommendations regarding model architecture, deployment strategy, and solution design for business use cases.

AI Solution Design & Enablement

  • Partner with business units and technology teams to identify, define, and evaluate AI use cases.
  • Translate business requirements into technical specifications and AI solution recommendations.
  • Design and evaluate prompting, retrieval-augmented generation (RAG), fine-tuning, and model orchestration approaches when appropriate.
  • Support implementation of AI-enabled applications, workflows, copilots, agents, and knowledge management solutions.
  • Collaborate with AI Engineers and solution teams to ensure effective deployment and adoption of AI solutions.

Cost Optimization & Value Realization

  • Evaluate and communicate cost implications associated with AI platforms, models, and deployment approaches.
  • Analyze token consumption, inference costs, hosting models, licensing structures, and operational expenses.
  • Develop financial analyses and cost models that enable business stakeholders to make informed investment decisions.
  • Recommend optimization strategies that balance business value, performance, scalability, and cost efficiency.

Security, Privacy & Risk Management

  • Assess security risks associated with LLM implementations, including prompt injection, data leakage, unauthorized access, model misuse, adversarial attacks, and other emerging threats.
  • Collaborate with Information Security, Risk Management, Compliance, and Legal teams to ensure AI solutions operate within established enterprise standards and policies.
  • Support the evaluation of AI solutions for privacy, security, and regulatory compliance requirements.
  • Participate in risk identification, mitigation planning, monitoring activities, and remediation efforts related to AI technologies.
  • Assist in establishing controls that support responsibility and secure AI deployment across the enterprise.

Monitoring & Continuous Improvement

  • Monitor AI model performance, effectiveness, reliability, and operational outcomes after deployment.
  • Identify performance degradation, emerging vulnerabilities, and opportunities for improvement.
  • Recommend model updates, technology enhancements, and alternative solutions as AI capabilities evolve.
  • Maintain awareness of advancements in Generative AI, LLMs, model evaluation methodologies, and industry best practices.

Education & Knowledge Sharing

  • Develop guidance, standards, job aids, and documentation related to LLM usage and Generative AI best practices.
  • Educate business and technical stakeholders on AI capabilities, limitations, risks, and responsible usage considerations.
  • Support AI literacy efforts and enterprise training initiatives.
  • Serve as a trusted advisor and technical resource for enterprise AI initiatives.

Compliance

  • Maintain knowledge of and ensure adherence to all applicable federal and state laws, regulations, and PenFed policies, procedures, and standards.
  • Support compliance with enterprise AI management, information security, privacy, risk management, and data governance requirements.
  • Assist with internal audits, regulatory examinations, and independent reviews related to AI technologies.
  • Promote responsible AI practices consistently with PenFed's ethical, security, compliance, and risk management objectives.

Qualifications

Equivalent combination of education and experience is considered.

  • Bachelor’s degree in computer science, Data Science, Information Systems, Engineering, Artificial Intelligence, or a related field required.
  • Advanced degree preferred.
  • Minimum of 4 years of experience working directly with Generative AI, Large Language Models, Machine Learning, or related technologies.
  • Experience evaluating and implementing solutions across multiple LLM platforms and model providers.
  • Demonstrated experience supporting AI solution design, deployment, and operationalization.
  • Experience communicating technical topics to business stakeholders and executive audiences.
  • Financial services experience preferred.
  • Strong understanding of Large Language Models, Generative AI technologies, foundation models, and emerging AI architectures.
  • Knowledge of prompt engineering, retrieval-augmented generation (RAG), embeddings, vector databases, model evaluation, and fine-tuning approaches.
  • Understanding of AI security risks, including prompt injection, adversarial attacks, data privacy concerns, access controls, and secure integration practices.
  • Familiarity with AI governance, responsible AI principles, privacy requirements, and risk management considerations.
  • Knowledge of model performance evaluation techniques, benchmarking methodologies, and LLMOps/MLOps practices.
  • Ability to evaluate and communicate cost, performance, security, and scalability tradeoffs associated with AI solutions.
  • Strong analytical, problem-solving, and critical thinking skills.
  • Excellent verbal, written, presentation, and stakeholder management skills.
  • Ability to translate complex technical concepts into clear business-oriented recommendations.
  • Ability to work effectively across technical, business, compliance, risk, and leadership teams.
  • Strong organizational skills with the ability to manage multiple priorities in a fast-paced environment.

Supervisory Responsibility

This position will not supervise employees.

Licenses and Certifications

There are no additional certifications required.
 

Work Environment

While performing the duties of this job, the employee is regularly exposed to an indoor office setting with moderate noise.

*Most roles require working in an office setting with moderate noise and the ability to lift 25 pounds.*

Travel

Ability to travel to various worksites and be on call will be required.

Pay Transparency 
The anticipated starting salary range for this role is $79,400.00 - $161,041.00
This position is eligible for an organizational performance based annual bonus, subject to board discretion and approval.
This position is eligible for an individual performance based annual bonus.

#LI-Hybrid

Qualifications:

Equivalent combination of education and experience is considered.

  • Bachelor’s degree in computer science, Data Science, Information Systems, Engineering, Artificial Intelligence, or a related field required.
  • Advanced degree preferred.
  • Minimum of 4 years of experience working directly with Generative AI, Large Language Models, Machine Learning, or related technologies.
  • Experience evaluating and implementing solutions across multiple LLM platforms and model providers.
  • Demonstrated experience supporting AI solution design, deployment, and operationalization.
  • Experience communicating technical topics to business stakeholders and executive audiences.
  • Financial services experience preferred.
  • Strong understanding of Large Language Models, Generative AI technologies, foundation models, and emerging AI architectures.
  • Knowledge of prompt engineering, retrieval-augmented generation (RAG), embeddings, vector databases, model evaluation, and fine-tuning approaches.
  • Understanding of AI security risks, including prompt injection, adversarial attacks, data privacy concerns, access controls, and secure integration practices.
  • Familiarity with AI governance, responsible AI principles, privacy requirements, and risk management considerations.
  • Knowledge of model performance evaluation techniques, benchmarking methodologies, and LLMOps/MLOps practices.
  • Ability to evaluate and communicate cost, performance, security, and scalability tradeoffs associated with AI solutions.
  • Strong analytical, problem-solving, and critical thinking skills.
  • Excellent verbal, written, presentation, and stakeholder management skills.
  • Ability to translate complex technical concepts into clear business-oriented recommendations.
  • Ability to work effectively across technical, business, compliance, risk, and leadership teams.
  • Strong organizational skills with the ability to manage multiple priorities in a fast-paced environment.

Supervisory Responsibility

This position will not supervise employees.

Licenses and Certifications

There are no additional certifications required.
 

Work Environment

While performing the duties of this job, the employee is regularly exposed to an indoor office setting with moderate noise.

*Most roles require working in an office setting with moderate noise and the ability to lift 25 pounds.*

Travel

Ability to travel to various worksites and be on call will be required.

Pay Transparency 
The anticipated starting salary range for this role is $79,400.00 - $161,041.00
This position is eligible for an organizational performance based annual bonus, subject to board discretion and approval.
This position is eligible for an individual performance based annual bonus.

#LI-Hybrid

Education:UNAVAILABLEEmployment Type: FULL_TIME

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