AI Engineer

Job Title: AI Engineer

Location: Edison NJ (Hybrid/On-site)

Full-time

About the Role:

We are looking for a highly skilled AI Engineer with 5 7 years of experience in building deploying and optimizing machine learning and generative AI solutions. The ideal candidate has strong expertise in Python modern ML frameworks and hands-on experience with Large Language Models (LLMs) RAG pipelines and LangChain. You will work closely with data scientists software engineers and business teams to build scalable AI-driven applications and automation solutions.

Key Responsibilities:

• Design develop and deploy AI/ML models including deep learning and NLP-based systems.
• Build and optimize LLM-powered applications including custom model fine-tuning prompt engineering and evaluation.
• Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases and retrieval frameworks.
• Build scalable LangChain-based applications and agents to orchestrate LLM workflows.
• Implement and maintain end-to-end ML pipelines supporting training inference and continuous model improvement.
• Develop clean scalable Python code for AI/ML features automation and backend logic.
• Integrate LLMs with enterprise data sources APIs and cloud platforms.
• Evaluate benchmark and optimize model performance latency and reliability.
• Collaborate with product engineering and data teams to design AI-driven features and system architectures.
• Ensure security compliance and responsible use of AI in production systems.

Required Qualifications:

• 5 7 years of experience in AI Engineering ML Engineering or similar roles.
• Strong proficiency in Python and related ML/NLP libraries (TensorFlow PyTorch Scikit-learn Transformers etc.).
• Hands-on experience working with Large Language Models (OpenAI Anthropic Llama Mistral etc.).
• Experience building RAG systems using vector databases (FAISS Pinecone Weaviate Milvus Chroma etc.).
• Practical experience with LangChain LlamaIndex or other LLM orchestration frameworks.
• Strong understanding of prompt engineering embeddings tokenization and LLM evaluation.
• Experience deploying AI models into production using cloud platforms (Azure AWS GCP).
• Familiarity with modern MLOps practices-model versioning CI/CD monitoring and drift detection.
• Strong understanding of APIs microservices and integration patterns.
• Excellent problem-solving debugging and communication skills.

Preferred Skills:

• Experience with Docker Kubernetes or serverless deployments.
• Familiarity with Databricks Spark or distributed compute environments.
• Experience with tools like Hugging Face Hub OpenAI Assistants API or LangGraph.
• Background in vector search optimization embedding models and document chunking strategies.
• Knowledge of security compliance and responsible AI practices.

Education:

Bachelors or Masters degree in Computer Science Data Science AI/ML Engineering or a related field (or equivalent practical experience).