Remote LLM Architect & AI Solutions Lead

eSimplicity Inc.; Columbia, Northern (MD, KY); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

401(k) retirement benefits

Paid time off

Paid holidays

Life and disability insurance

Wellness programs

Job summary

eSimplicity Inc. is seeking an LLM Specialist to drive design, development, and deployment of advanced language-model capabilities across a cloud analytics ecosystem.

You will own architecture for fine-tuning, RAG, agentic frameworks, and domain adaptation, guiding prototypes and scalable pipelines with emphasis on governance and security. The role collaborates with engineering, product, and data teams to push safe, effective generative AI deployment and transformation for federal and government

Qualifications

• Bachelor's degree in a technical field with 5+ years in software/AI/ML.
• Experience designing, developing, and supporting LLM/Generative AI solutions.
• Experience with fine-tuning, prompt engineering, and evaluation methods.
• Experience designing RAG solutions and retrieval pipelines.
• Proficiency in Python and LLM frameworks; cloud deployment experience.

Responsibilities

• Design, develop, and operationalize advanced LLM capabilities across a cloud analytics ecosystem.
• Lead architecture and strategy for fine-tuning, RAG, and domain adaptation.
• Guide development of high-impact prototypes and scalable LLM pipelines.
• Ensure governance, security, and performance across model implementations.

Skills

Python

LangChain

LlamaIndex

Cloud platforms

MLOps

CI/CD

Security

Data governance

RAG pipelines

Education

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems

Tools

LangChain

LlamaIndex

Vector databases

Embeddings

Databricks

Snowflake

Job description

eSimplicity Inc. is seeking an LLM Specialist to drive design, development, and deployment of advanced language-model capabilities across a cloud analytics ecosystem.

You will own architecture for fine-tuning, RAG, agentic frameworks, and domain adaptation, guiding prototypes and scalable pipelines with emphasis on governance and security. The role collaborates with engineering, product, and data teams to push safe, effective generative AI deployment and transformation for federal and government