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Llm Delivery Jobs (NOW HIRING)

Senior Software Engineer - TensorRT Edge-LLM

Austin, TX ยท Hybrid

$121.40K - $160.10K/yr

Join NVIDIA's TensorRT Edge-LLM team and help shape the next generation of edge AI for automotive ... Collaborate with teams across CUDA, kernel libraries, compilers, and robotics to deliver high ...

OR ยท Hybrid

$122.40K - $161.30K/yr

Join NVIDIA's TensorRT Edge-LLM team and help shape the next generation of edge AI for automotive ... Collaborate with teams across CUDA, kernel libraries, compilers, and robotics to deliver high ...

As part of our growth strategy, we're expanding our AI capabilities to deliver cutting-edge ... As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ...

As part of our growth strategy, we're expanding our AI capabilities to deliver cutting-edge ... As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ...

As part of our growth strategy, we're expanding our AI capabilities to deliver cutting-edge ... As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ...

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Llm Delivery information

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$13

$46

$91

How much do llm delivery jobs pay per hour?

As of May 29, 2026, the average hourly pay for llm delivery in the United States is $46.36, according to ZipRecruiter salary data. Most workers in this role earn between $20.43 and $60.58 per hour, depending on experience, location, and employer.

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

To thrive as an LLM Delivery specialist, you need a strong background in machine learning, natural language processing, and software engineering, often supported by a degree in computer science or a related field. Familiarity with large language model frameworks (such as OpenAI, Hugging Face), cloud platforms, and MLOps tools is typically required, along with experience in model deployment and monitoring. Excellent problem-solving skills, effective communication, and adaptability are vital soft skills for collaborating with cross-functional teams and addressing client needs. These competencies ensure successful implementation, scalability, and optimization of language model solutions in dynamic production environments.

What are some common challenges faced by professionals in LLM Delivery roles, and how can they be addressed?

Professionals in LLM Delivery often encounter challenges such as aligning large language model solutions with client requirements, managing cross-functional teams, and ensuring robust model deployment and monitoring. Successfully navigating these challenges typically involves clear communication with stakeholders, staying updated on best practices in AI model deployment, and collaborating closely with data scientists, engineers, and product managers. Building strong project management skills and fostering a culture of continuous feedback can also help in delivering high-quality, scalable LLM solutions.

What is an LLM Delivery specialist?

An LLM Delivery specialist is a professional responsible for deploying, integrating, and maintaining large language models (LLMs) within an organization or for clients. Their work involves overseeing the effective implementation of LLM solutions, ensuring they meet business requirements, and handling issues like scalability, data privacy, and performance optimization. They often collaborate with data scientists, engineers, and stakeholders to deliver AI-driven applications and services powered by LLMs.

What is the difference between Llm Delivery vs Data Scientist?

AspectLlm DeliveryData Scientist
Required CredentialsTypically requires knowledge of AI/ML deployment, cloud platforms, and programming skillsRequires degrees in data science, statistics, or related fields, with skills in programming and analytics
Work EnvironmentOften involves collaboration with AI teams, cloud infrastructure, and client-facing projectsWorks with data analysis, modeling, and visualization within teams or independently
Employer & Industry UsageUsed in tech companies, AI service providers, and consulting firmsCommon in tech, finance, healthcare, and research organizations
Search & Comparison IntentPeople compare roles related to AI deployment and implementationPeople compare roles focused on data analysis and modeling

While both roles involve technical skills, Llm Delivery focuses on deploying large language models and AI solutions, whereas Data Scientists primarily analyze data and build predictive models. Understanding these differences helps candidates choose the right career path or job opportunity.

More about Llm Delivery jobs
What cities are hiring for Llm Delivery jobs? Cities with the most Llm Delivery job openings:
What states have the most Llm Delivery jobs? States with the most job openings for Llm Delivery jobs include:
Infographic showing various Llm Delivery job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 65% Full Time, 30% Part Time, and 4% Contract. Highlights an 38% Physical, 50% Hybrid, and 12% Remote job distribution, with an average salary of $96,421 per year, or $46.4 per hour.
Staff Software Development Engineer (LLM)

Staff Software Development Engineer (LLM)

Fortinet, Inc.

Sunnyvale, CA โ€ข On-site

$196.50K - $219.30K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago


Job description

Job Responsibilities:

  1. Architect and implement functions to monitor and filter LLM requests/responses in real time, preventing prompt injection attacks and unauthorized data leakage.
  2. Build a highly scalable pipeline capable of handling high-volume LLM traffic with low latency, including optimizing databases and caching for quick threat detection and response.
  3. Develop monitoring, logging, and alerting systems to detect anomalies in LLM usage (e.g. suspicious spikes indicating denial-of-service attacks or unusual prompt patterns indicating misuse).
  4. Collaborate with teams to translate security requirements into platform features. Mentor junior engineers on secure backend development and best practices in an Agile environment.
  5. Ensure the timely delivery of high-quality software features while adhering to project schedules.ย 
  6. Communicate effectively across teams, with both technical and non-technical stakeholders, in both verbal and written forms.ย 

Job requirements:

  1. Hands-on experience with deploying or integrating large language models or other AI/ML systems (e.g. implementing model inference pipelines, fine-tuning models, or working with LLM APIs and prompt handling). Strong understanding of how prompts and context are managed in LLM applications.
  2. Solid knowledge of application security principles and experience building secure systems. Familiarity with AI-specific threats (prompt injection, data poisoning, output manipulation) and a keen interest in staying ahead of new generative AI attack vectors.
  3. Proven experience designing microservices architectures and using containerization (Docker) and orchestration (Kubernetes). Comfortable with cloud platforms (AWS, GCP, or Azure) and designing observable, resilient services in a production environment.
  4. Ability to design clean, efficient, and secure APIs. Strong understanding of network protocols, data caching, and performance optimization.
  5. Knowledge of data protection and privacy best practices - able to design systems that handle sensitive data responsibly and comply with regulations. Understanding of responsible AI principles (ethics, bias, transparency) and how they relate to secure AI system design.
  6. Familiarity with emerging AI security guidelines such as OWASP's Top 10 for LLMs/Generative AI Security (e.g. knowledge of prompt injection, insecure output handling, data poisoning risks) and experience implementing related mitigations.
  7. Experience with retrieval-augmented generation (RAG) architectures, vector databases/embedding stores, or streaming data pipelines for ML - especially as they relate to monitoring and securing LLM workflows (helps in addressing vector embedding attack vulnerabilities).
  8. Understanding of responsible AI and techniques for detecting AI-generated misinformation or hallucinations. Experience building or integrating content filtering, policy enforcement, or fact-checking systems in AI applications is a plus.
  9. Strong programming and debugging skills, particularly in Python and C/C++.ย 
  10. Familiarity with Frameworks like PyTorch or TensorFlow for model integration; libraries such as Hugging Face Transformers or LangChain for LLM and prompt management; LLM APIs (OpenAI, etc.) and vector databases is beneficial.

The US base salary range for this full-time position is $196,500-$219,300. Fortinet offers employees a variety of benefits, including medical, dental, vision, life and disability insurance, 401(k), 11 paid holidays, vacation time, and sick time as well as a comprehensive leave program.

Wage ranges are based on various factors including the labor market, job type, and job level. Exact salary offers will be determined by factors such as the candidate's subject knowledge, skill level, qualifications, experience, and geographic location.

All roles are eligible to participate in the Fortinet equity program, Bonus eligibility is reviewed at time of hire and annually at the Company's discretion.

Why Join Us:
We encourage candidates from all backgrounds and identities to apply. We offer a supportive work environment and a competitive Total Rewards package to support you with your overall health and financial well-being. Embark on a challenging, enjoyable, and rewarding career journey with Fortinet. Join us in bringing solutions that make a meaningful and lasting impact to our 660,000+ customers around the globe.

Fortinet (NASDAQ: FTNT) secures the largest enterprise, service provider, and government organizations around the world. Fortinet empowers its customers with intelligent, seamless protection across the expanding attack surface and the power to take on ever-increasing performance requirements of the borderless network - today and into the future. Only the Fortinet Security Fabric architecture can deliver security without compromise to address the most critical security challenges, whether in networked, application, cloud or mobile environments. Fortinet ranks number one in the most security appliances shipped worldwide and more than 500,000 customers trust Fortinet to protect their businesses.

We are committed to providing reasonable accommodations for all qualified individuals with disabilities. If you require assistance or accommodation due to a disability, please contact us at accommodations@fortinet.com.
ย 
Fortinet is an equal opportunity employer. We value diversity in our company, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, military/veteran status or any other applicable legally protected characteristics in the location in which the candidate is applying.