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Artificial Intelligence Llm Jobs (NOW HIRING)

Long Finch Technologies

Artificial Intelligence Architect Java 21+, Spring Boot, Spring AI Microservices, event-driven ... LLM integration via Anthropic Claude API, OpenAI, or AWS Bedrock RAG architectures, vector ...

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Artificial Intelligence Llm information

What is an artificial intelligence LLM?

An Artificial Intelligence LLM (Large Language Model) is a type of AI system designed to understand, generate, and interact with human language. These models are trained on vast amounts of text data and can perform tasks such as answering questions, writing content, translating languages, and more. LLMs use advanced machine learning techniques, particularly deep learning, to process and generate human-like responses. They play a significant role in applications like chatbots, virtual assistants, and automated content creation.

What are the key skills and qualifications needed to thrive as an artificial intelligence LLM engineer?

To thrive as an AI LLM Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree and experience with AI model development. Proficiency with frameworks such as TensorFlow or PyTorch, knowledge of deep learning architectures, and familiarity with cloud computing platforms are typically required. Analytical thinking, problem-solving, and effective collaboration are crucial soft skills that set professionals apart in this field. These skills and qualities are vital for designing, optimizing, and deploying advanced language models that meet real-world needs and deliver reliable AI solutions.

What are some common challenges artificial intelligence LLM professionals face when deploying large language models in production environments?

Artificial Intelligence LLM professionals often encounter challenges such as ensuring model scalability, managing computational resource costs, and addressing data privacy concerns when deploying large language models. Additionally, monitoring model performance and mitigating bias or unintended outputs are crucial ongoing tasks. Collaboration with engineering, data, and product teams is essential to align technical capabilities with business needs and maintain reliable, ethical AI outputs in real-world applications.

Is artificial intelligence Llm a good career?

Artificial Intelligence Large Language Model (LLM) development is a growing field with high demand for skilled professionals in machine learning, data science, and programming. Careers in AI often require knowledge of programming languages like Python, experience with neural networks, and familiarity with AI frameworks such as TensorFlow or PyTorch. The field offers opportunities in research, development, and deployment across various industries, with competitive salaries and ongoing learning requirements.

What jobs can I do with artificial intelligence Llm?

Artificial Intelligence LLM (Large Language Model) expertise can lead to roles such as AI researcher, machine learning engineer, data scientist, NLP engineer, and AI product manager. These jobs typically involve developing, deploying, and maintaining AI models, requiring skills in programming, data analysis, and understanding of AI frameworks like TensorFlow or PyTorch.
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Artificial Intelligence Llm jobs near you
Infographic showing various Artificial Intelligence Llm job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

Artificial Intelligence Architect

O Fallon, MO • On-site

Long Finch Technologies
IT Services • 51 - 200 employees
Learn more about Long Finch Technologiesexternal

Full-time

Posted 11 days ago

Job description

NEED ONLY USC/GC. CAN WORK FROM ANY NEARBY OFFICE. NO NEED TO RELOCATE TO A DIFFERENT PLACE

WE ARE LOOKING FOR ARCHITECT FOR THIS POSITION NOT DEVELOPER.

Artificial Intelligence Architect

Java 21+, Spring Boot, Spring AI
Microservices, event-driven architecture (Kafka, SQS/SNS)
REST/GraphQL API design, gRPC
Design patterns, Enterprise architecture and scaling
AI / ML Integration
Experience with Agentic AI / multi-agent frameworks at enterprise scale.
LLM integration via Anthropic Claude API, OpenAI, or AWS Bedrock
RAG architectures, vector databases (OpenSearch, Pinecone, pgvector)
Model serving, inference optimization, prompt engineering
Spring AI, Langgraph, Google ADK, A2A, MCP.
Prompt Engineering, prompt caching, Token optimization.
AWS

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