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Full Time Llm Engineer Jobs (NOW HIRING)

Northern Base

AI/LLM Engineer

New York, NY · On-site

Edison, NY (Hybrid - 3 Days Onsite) Employment Type: Full-Time Experience Required: 8-10 Years Visa ... AI/LLM Engineering * Python Development * LangChain * LangGraph * Agent-Based AI Systems

USA Clinics Group

LLM Engineer

Northbrook, IL · On-site

$85K - $115K/yr

The LLM Engineer serves as the organization's AI technical lead responsible for designing ... Schedule: Full-time, Monday through Friday on-site. * Compensation: $85,000 - $115,000 Key ...

USA Clinics Group

LLM Engineer

Northbrook, IL · On-site

$85K - $115K/yr

The LLM Engineer serves as the organization's AI technical lead responsible for designing ... Schedule: Full-time, Monday through Friday on-site. * Compensation: $85,000 - $115,000 Key ...

CVS Health

AI/LLM Engineer

Hartford, CT · On-site

$101K - $203K/yr

We are seeking an experienced AI / LLM Engineer to design, develop, and operationalize advanced ... This fulltime position is eligible for a comprehensive benefits package designed to support the ...

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Full Time Llm Engineer information

What are the key skills and qualifications needed to thrive as a full time LLM engineer?

To thrive as a Full Time 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 large language models. Familiarity with frameworks such as PyTorch or TensorFlow, version control systems like Git, and experience deploying models using cloud platforms or MLOps tools are typically required. Strong problem-solving, collaboration, and communication skills help you work effectively within cross-functional teams and adapt to evolving technologies. These skills ensure the design, optimization, and deployment of robust language models that meet real-world application needs.

What are some common challenges faced by full time LLM engineers when deploying large language models in production environments?

Full Time LLM Engineers often encounter challenges related to optimizing model performance, managing infrastructure costs, and ensuring reliable scaling in production. Handling inference speed and latency is critical, especially when integrating with real-time applications. Additionally, monitoring model behavior for biases, drift, and security vulnerabilities requires ongoing collaboration with data scientists and operations teams. Staying updated on the latest advancements and tools in the LLM landscape is essential for maintaining effective and efficient deployments.

What is a full time LLM engineer?

Full Time LLM Engineers are professionals who specialize in developing, fine-tuning, and deploying large language models (LLMs) like GPT, BERT, or similar AI models. They work with machine learning frameworks, manage data pipelines, and optimize model performance for various applications such as chatbots, content generation, and natural language processing tasks. These engineers often collaborate with data scientists, product teams, and software engineers to integrate LLMs into products and services. Their responsibilities may also include monitoring model outputs, ensuring ethical AI use, and staying updated with advancements in the field.

What is the difference between Full Time Llm Engineer vs Machine Learning Engineer?

AspectFull Time Llm EngineerMachine Learning Engineer
Required CredentialsAdvanced degree in law, computer science, or related fields; knowledge of legal data and NLPDegree in computer science, data science, or related fields; expertise in algorithms and data modeling
Work EnvironmentLegal tech companies, AI firms focusing on legal applications, research institutionsTech companies, startups, research labs working on AI and data-driven solutions
Employer & Industry UsageLegal industry, AI legal tools, compliance firmsTechnology industry, AI product development, data-driven applications

While both roles involve AI and data, a Full Time Llm Engineer specializes in legal language models and legal data, whereas a Machine Learning Engineer works broadly across various AI applications and industries. The Llm Engineer focuses on legal-specific NLP tasks, requiring legal knowledge combined with AI skills, while the Machine Learning Engineer has a broader scope in AI development across sectors.

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Full Time Llm Engineer jobs near you
Infographic showing various Full Time Llm Engineer job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution.

AI/LLM Engineer

Northern Base

New York, NY • On-site

Full-time

Posted 4 days ago

Job description

Hiring Alert | AI/LLM Engineer
Location: Edison, NY (Hybrid – 3 Days Onsite)
Employment Type: Full-Time
Experience Required: 8–10 Years
Visa Type: USC / GC Only

Interview Mode: In-person (Final Round in New York City, NY / Edison, NJ)

Must-Have Skills:
• AI/LLM Engineering
• Python Development
• LangChain
• LangGraph
• Agent-Based AI Systems
• Autonomous AI Agents
• ReAct (Reasoning + Acting)
• LLM Reasoning, Planning & Task Execution
• Model Context Protocol (MCP)
• Tool Calling & Tool Integration
• LLM Workflow Chaining & Orchestration
• Memory & Context Management
• Prompt Engineering Collaboration
• Async Python Programming
• API & Microservices Development
• Scalable AI Application Architecture
• LLM Guardrails & Safety Mechanisms
• Responsible AI & Edge Case Handling
• Snowflake
• Databricks
• Lakehouse Architecture
• Enterprise Data Platform Integration

Preferred Experience:
• Experience designing and building production-ready agentic AI systems
• Experience with LangChain, LangGraph, or similar agent frameworks
• Experience implementing autonomous reasoning and planning capabilities
• Experience integrating LLMs with enterprise tools and data platforms
• Experience developing scalable APIs and microservices for AI applications
• Experience implementing guardrails and responsible AI practices
• Experience with Snowflake and Databricks data platforms
• Experience with Lakehouse architectures and enterprise data pipelines
• Strong understanding of LLM orchestration patterns and agent workflows
• Strong problem-solving and communication skills
• Willingness to work from the Edison office 3 days per week
• Ability to attend an in-person F2F interview in Edison

Education:
Bachelor’s Degree in Computer Science or related field preferred.

Tech Stack:
Python | LangChain | LangGraph | LLMs | Agentic AI | AI Agents | ReAct | MCP | Tool Calling | LLM Orchestration | Prompt Engineering | Async Python | APIs | Microservices | AI Guardrails | Responsible AI | Snowflake | Databricks | Lakehouse | Data Pipelines | Enterprise AI | AI System Architecture