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Llm Delivery Jobs (NOW HIRING)

Our mission is simple: deliver life-changing, minimally invasive care, close to home. We're ... The LLM Engineer serves as the organization's AI technical lead responsible for designing ...

LLM Engineer

Northbrook, IL ยท On-site

$85K - $115K/yr

Our mission is simple: deliver life-changing, minimally invasive care, close to home. We're ... The LLM Engineer serves as the organization's AI technical lead responsible for designing ...

Sr. AI/ML Engineer (LLM)

Miami, FL ยท On-site

$99K - $137K/yr

We are a family-owned and operated business that has been delivering excellence in the automotive ... Ensure that LLM integrations are efficient, scalable, and secure, adhering to industry best ...

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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 Aug 23, 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 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 are the key skills and qualifications needed to thrive as an LLM Delivery specialist?

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 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 August 2026, with employment types broken down into 1% As Needed, 63% Full Time, 32% Part Time, and 4% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $96,421 per year, or $46.4 per hour.

Google Cloud Platform LLM Agentic AI Solution Architect

ERPMark Inc

Santa Clara, CA โ€ข On-site

$73.50 - $96.75/hr

Other

Posted 5 days ago


Job description

Google Cloud Platform LLM Agentic AI Solution Architect โ€“ Dice Job Posting

Job Title: Google Cloud Platform LLM Agentic AI Solution Architect
Location: Santa Clara, CA โ€“ Onsite
Experience: 10โ€“12+ Years

Position Overview

We are looking for an experienced LLM & Agentic AI Solution Architect to lead the architecture and delivery of enterprise-grade Generative AI and Agentic AI solutions across Azure and Google Cloud Platform environments.

The ideal candidate will have strong hands-on experience with Azure OpenAI, Azure AI Studio, Google Cloud Platform Vertex AI, LLM orchestration, RAG, LangChain/LangGraph, Kubernetes, cloud functions, APIs, and enterprise integrations.

Mandatory Skills
  • Generative AI / LLM Solution Architecture โ€“ 2โ€“3+ years

  • Agentic AI and Multi-Agent Architecture โ€“ 2โ€“3+ years

  • RAG Architecture and Data Pipeline Design โ€“ 2โ€“3+ years

  • LLM Orchestration using LangChain, LangGraph, AutoGen, or DSPy

  • Azure OpenAI and Azure AI Studio โ€“ 2โ€“3+ years

  • Google Cloud Platform Vertex AI โ€“ 2โ€“3+ years

  • Python-based Microservices and Backend Architecture โ€“ 5+ years

  • Azure Functions / Google Cloud Platform Cloud Functions

  • Kubernetes and Cloud-Native Architecture

  • Enterprise APIs and Custom Connector Integrations

  • API Management using Azure APIM, Apigee, or MuleSoft

  • Vector Databases/Search โ€“ Azure Cognitive Search, Pinecone, Weaviate, FAISS, or Vertex AI Matching Engine

  • LLM Fine-Tuning / PEFT โ€“ LoRA, QLoRA, PEFT

  • LLM Memory Architecture โ€“ short-term, long-term, and episodic memory

  • LLM Performance Optimization โ€“ latency, throughput, scalability

  • LLM Governance, Security, Guardrails, and Responsible AI

Key Responsibilities
  • Architect scalable and secure LLM and Agentic AI solutions across Azure and Google Cloud Platform.

  • Design enterprise-grade RAG pipelines, AI assistants, and multi-agent applications.

  • Lead architecture for LLM orchestration, tool invocation, context management, and task decomposition.

  • Integrate Azure OpenAI, OpenAI, Google Cloud Platform Vertex AI, and third-party models into enterprise applications.

  • Define API, microservices, cloud-function, Kubernetes, and integration architectures.

  • Establish LLMOps/AgentOps practices including CI/CD, monitoring, observability, optimization, and cost management.

  • Implement responsible AI controls including prompt-injection protection, content moderation, data protection, and hallucination mitigation.

  • Lead architecture reviews, technical design authority, PoCs, and enterprise AI governance.

  • Partner with engineering, data science, product, and business teams to translate AI use cases into production-ready solutions.

  • Mentor engineering teams on LLM architecture, evaluation, performance tuning, and Agentic AI development.

Required Education

Bachelorโ€™s or Masterโ€™s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Preferred / Secondary Skills
  • MCP and A2A SDK knowledge

  • Git / Version Control

  • Agile / Scrum

  • Jira / Azure DevOps

  • BigQuery

  • Azure Cognitive Services

  • Azure Cognitive Search

  • Google Cloud Platform Matching Engine

  • LLM evaluation frameworks

  • AI observability and AgentOps

What Weโ€™re Looking For

Candidates should demonstrate hands-on, project-level experience with the required technologies. Primary skills and exact years of experience should be clearly reflected in the resume, particularly across relevant projects.

Interested candidates can share their updated resume with  


ERPMARK logo

About ERPMARK

Sourced by ZipRecruiter

Why Choose ERPMark PEOPLE We deliver the best available people to your most challenging IT positions when you need them. PROCESS Our rigorous processes enable us to not only bring the best available people to your business, but also deep experience in product development, CRM services, big data analytics and software testing. PERFORMANCE We will let our many Fortune 500 clients speak to our performance. We would not be working with so many great companies if we did not deliver what we promise.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Princeton, NJ, US

Year founded

2014