AI Engineer Only on W2 USC

We are seeking a highly skilled AI Engineer to design, develop, and deploy AI-powered applications and machine learning solutions. The ideal candidate will have experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), cloud platforms, and modern AI frameworks. You will work closely with cross-functional teams to build scalable AI solutions that solve real-world business problems.

Key Responsibilities

• Design, develop, and deploy AI/ML and Generative AI applications.
• Build and optimize LLM-powered solutions using OpenAI, Claude, Gemini, or similar models.
• Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Create AI agents and workflow automation solutions.
• Fine-tune, evaluate, and optimize AI models for performance and accuracy.
• Build RESTful APIs and microservices to integrate AI capabilities into enterprise applications.
• Develop data preprocessing and feature engineering pipelines.
• Collaborate with data scientists, software engineers, and product teams.
• Deploy AI solutions on AWS, Azure, or Google Cloud Platform.
• Monitor, troubleshoot, and optimize AI applications in production.
• Follow MLOps best practices for model deployment, monitoring, and lifecycle management.

Required Skills

Programming Languages

• Python (Required)
• Java (Preferred)
• SQL

AI & Machine Learning

• Machine Learning
• Deep Learning
• Natural Language Processing (NLP)
• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• AI Agents
• Fine-Tuning
• Model Evaluation

AI Frameworks & Libraries

• LangChain
• LangGraph
• LlamaIndex
• Hugging Face Transformers
• TensorFlow
• PyTorch
• Scikit-learn
• OpenAI API
• Anthropic Claude API
• Google Gemini API

RAG & Vector Databases

• Retrieval-Augmented Generation (RAG)
• Pinecone
• Weaviate
• ChromaDB
• FAISS
• Milvus

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (Google Cloud Platform)

Databases

• PostgreSQL
• MongoDB
• MySQL
• Redis

DevOps & MLOps

• Docker
• Kubernetes
• Git
• GitHub/GitLab
• Jenkins
• MLflow
• Kubeflow
• CI/CD Pipelines

API & Backend

• FastAPI
• Flask
• REST APIs
• GraphQL
• Microservices

Qualifications

• Bachelor''''''''s or Master''''''''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 6+ years of software engineering experience with at least 2+ years in AI/ML or Generative AI.
• Strong proficiency in Python programming.
• Experience building and deploying production-grade AI applications.
• Hands-on experience with LLMs, RAG, and prompt engineering.
• Experience with cloud platforms and containerization technologies.
• Excellent analytical, problem-solving, and communication skills.