Artificial Intelligence Engineer

Rsa Tech Group; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Rsa Tech Group seeks an experienced AI Engineer to design, develop, and deploy AI/ML models addressing complex business challenges. You will build Generative AI apps using LLMs and integrate LangChain/LlamaIndex into production systems. Collaboration with OpenAI, Azure OpenAI, Hugging Face, and other AI platforms is essential.

You will architect RAG pipelines, vector databases, and scalable deployments across cloud environments, ensuring performance, security, and alignment with enterprise needs.

Qualifications

• 5+ years of experience in AI/ML engineering or related roles.
• Strong programming experience in Python.
• Hands-on experience with Machine Learning and Deep Learning.
• Experience with Generative AI, LLMs, and Prompt Engineering.
• Knowledge of LangChain, LlamaIndex, and RAG architectures.
• Experience with TensorFlow, PyTorch, or Scikit-learn.
• Familiarity with vector databases such as Pinecone, FAISS, or ChromaDB.
• Experience with REST APIs, Microservices, and model deployment.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Understanding of NLP, model optimization, and AI security best practices.

Responsibilities

• Design, develop, and deploy AI/ML models to solve complex business problems.
• Build and implement Generative AI applications using Large Language Models (LLMs).
• Develop AI-powered solutions using frameworks such as LangChain and LlamaIndex.
• Work with OpenAI, Azure OpenAI, Hugging Face, and other AI platforms.
• Build Retrieval-Augmented Generation (RAG) pipelines and integrate vector databases.
• Develop and optimize machine learning and deep learning models.
• Implement prompt engineering, fine-tuning, and model evaluation techniques.
• Integrate AI models with enterprise applications, APIs, and cloud platforms.
• Optimize AI model performance, scalability, accuracy, and deployment.
• Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.

Skills

AI/ML engineering

ML/DL expertise

Generative AI

LLMs

Prompt engineering

NLP knowledge

Tools

Python

LangChain

LlamaIndex

TensorFlow

PyTorch

Scikit-learn

Pinecone

FAISS

ChromaDB

REST APIs

Microservices

AWS

Azure

GCP

OpenAI

Hugging Face

Job description

Our client is looking for an experienced AI Engineer with 5+ years of hands-on experience in designing, developing, and deploying AI-powered solutions. The ideal candidate should have strong expertise in Machine Learning, Generative AI, Large Language Models (LLMs), and Python-based AI development.

Key Responsibilities

• Design, develop, and deploy AI/ML models to solve complex business problems.
• Build and implement Generative AI applications using Large Language Models (LLMs).
• Develop AI-powered solutions using frameworks such as LangChain and LlamaIndex.
• Work with OpenAI, Azure OpenAI, Hugging Face, and other AI platforms.
• Build Retrieval-Augmented Generation (RAG) pipelines and integrate vector databases.
• Develop and optimize machine learning and deep learning models.
• Implement prompt engineering, fine-tuning, and model evaluation techniques.
• Integrate AI models with enterprise applications, APIs, and cloud platforms.
• Optimize AI model performance, scalability, accuracy, and deployment.
• Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.

Required Technical Skills

• 5+ years of experience in AI/ML engineering or related roles.
• Strong programming experience in Python.
• Hands-on experience with Machine Learning and Deep Learning.
• Experience with Generative AI, LLMs, and Prompt Engineering.
• Knowledge of LangChain, LlamaIndex, and RAG architectures.
• Experience with TensorFlow, PyTorch, or Scikit-learn.
• Familiarity with vector databases such as Pinecone, FAISS, or ChromaDB.
• Experience with REST APIs, Microservices, and model deployment.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Understanding of NLP, model optimization, and AI security best practices.

Preferred Qualifications

• Knowledge of MLOps, CI/CD, and containerization (Docker/Kubernetes).
• Experience with AI agents and multi-agent frameworks.
• Familiarity with data engineering and big data technologies