Generative AI Engineer | LLMs, RAG, MLOps

Artifintech; Houston (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Artifintech is seeking an experienced AI Engineer to design, develop, and deploy AI and ML solutions. The ideal candidate will have strong Python, ML, and cloud experience, with proficiency in TensorFlow, PyTorch, and Scikit-learn.

You will build generative AI solutions using LLMs, RAG pipelines, LangChain, and related frameworks, and deploy models via REST APIs. You will collaborate with data engineers and software teams to optimize performance, scalability, and governance, while implementing

Qualifications

• Proficiency in Python and ML frameworks.
• Experience deploying production AI/ML systems.
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Strong understanding of algorithms and model evaluation.

Responsibilities

• Design, develop, and deploy AI/ML models to solve business problems.
• Build scalable AI applications using Python and ML frameworks.
• Develop Generative AI solutions using LLMs and RAG pipelines.
• Implement prompt engineering to enhance model performance.
• Create AI-powered chatbots and automation solutions.
• Develop data preprocessing, feature engineering, and training pipelines.
• Integrate models with REST APIs and enterprise apps.
• Work with vector databases like Pinecone, FAISS, ChromaDB.
• Ensure security, governance, and responsible AI practices.

Skills

Python

SQL

Java

TensorFlow

PyTorch

Scikit-learn

LLMs

RAG

Prompt Engineering

LangChain

REST APIs

FastAPI

Flask

Education

Bachelor's or Master's degree in Computer Science / AI / Data Science

Job description

Artifintech is seeking an experienced AI Engineer to design, develop, and deploy AI and ML solutions. The ideal candidate will have strong Python, ML, and cloud experience, with proficiency in TensorFlow, PyTorch, and Scikit-learn.

You will build generative AI solutions using LLMs, RAG pipelines, LangChain, and related frameworks, and deploy models via REST APIs. You will collaborate with data engineers and software teams to optimize performance, scalability, and governance, while implementing