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# GenAI Engineer

- **Company:** InfiCare Inc
- **Location:** Jersey City, NJ, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Code Review, DevOps, Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, Reinforcement Learning, Google Cloud, Pytorch, Large Language Models, Snowflake, Deep Learning, Generative AI, Scikit Learn, Kubernetes, Variational Autoencoders, Machine Learning Operations, Virtual Agents, Api Design, GPT, Docker, Databricks, Microservices
- **Published:** June 29, 2026
- **Apply:** https://www.dice.com/job-detail/afda5492-cfe0-4b9a-916d-623dc62c762b

## About the Role

Our client is seeking a highly skilled Senior GenAI Engineer with a strong focus on Generative AI and Agentic development. The ideal candidate will design, develop, and implement Gen AI applications and algorithms that enhance enterprise AI capabilities, while serving as a hands-on engineering leader across multiple workstreams., * Strong knowledge of NLP, LLM app development, and Agentic Design

 * Experience developing multi-modal RAG systems for enterprise solutions
 * Proficiency in Python, R, or Java
 * Experience with TensorFlow, PyTorch, Scikit-learn, and OpenAI API
 * Cloud platforms: AWS, Azure, Google Cloud Platform, Snowflake, or Databricks
 * Containerization: Docker, Kubernetes; microservices architecture
 * Understanding of statistics, deep learning, GANs, VAEs, classification, regression, time series, reinforcement learning
 * Ability to design Agentic AI architecture, including context engineering and RAG

Preferred Skills

 * Expertise in RAG pipeline design and implementation.
 * Hands-on knowledge of Chain-of-Thought, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
 * Familiarity with the financial services industry.
 * DevOps practices and Agile methodologies.

## Description

* Design and develop scalable Gen AI and LLM/GenAI systems for complex business problems
 * Build, deploy, and operate production-grade ML and Generative AI services end-to-end
 * Build and institutionalize MLOps capabilities, including automated pipelines, monitoring, and model lifecycle management
 * Implement multi-modal RAG systems and Agentic AI architectures for enterprise solutions
 * Fine-tune and evaluate generative models (e.g., GPT-4.1) for NLP use cases, including summarization and text generation
 * Implement real-time model performance monitoring and optimization
 * Mentor and uplift junior engineers through design reviews, code reviews, and coaching
 * Communicate AI/ML capabilities and results to both technical and non-technical stakeholders


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