Gen AI Engineer
Propertyvalue Quantum Technologies Llc
New York, United States of America
yesterday
Role details
Contract type
Temporary contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
$ 196KJob location
New York, United States of America
Tech stack
API
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Data Security
Python
Open Source Technology
Performance Tuning
TensorFlow
Search Technologies
Google Cloud Platform
Enterprise Software Applications
PyTorch
Retrieval-Augmented Generation
Flask
Large Language Models
Prompt Engineering
Generative AI
GIT
FastAPI
Containerization
Kubernetes
Machine Learning Operations
REST
GPT
Docker
Job description
We are looking for a skilled Generative AI Engineer with strong Python expertise to design, develop, and deploy AI-driven solutions. The ideal candidate will have hands-on experience working with large language models (LLMs), prompt engineering, AI frameworks, and production-grade AI systems., * Design and develop Generative AI applications using Python.
- Work with LLMs (e.g., GPT-based models, open-source LLMs) for text generation, summarization, classification, and automation use cases.
- Implement prompt engineering techniques and optimize model outputs.
- Build AI pipelines using frameworks such as LangChain, LlamaIndex, or similar tools.
- Develop REST APIs to integrate AI models into enterprise applications.
- Work with vector databases (e.g., Pinecone, FAISS, Weaviate) for semantic search and RAG (Retrieval-Augmented Generation) systems.
- Fine-tune and evaluate models for performance, accuracy, and scalability.
- Deploy AI solutions on cloud platforms (AWS, Azure, or Google Cloud Platform).
- Collaborate with data engineers, product teams, and stakeholders to translate business requirements into AI solutions.
- Ensure responsible AI practices, including bias mitigation and data security.
Requirements
- Strong proficiency in Python.
- Experience with Generative AI / LLMs.
- Knowledge of NLP concepts.
- Hands-on experience with OpenAI APIs or similar LLM APIs.
- Experience with RAG architecture.
- Familiarity with Machine Learning frameworks (PyTorch / TensorFlow).
- Experience with REST APIs (FastAPI/Flask).
- Understanding of cloud platforms (AWS/Azure/Google Cloud Platform).
- Knowledge of Git and CI/CD pipelines.
Preferred Skills:
- Experience with fine-tuning LLMs.
- Knowledge of embeddings and vector search.
- Experience in BFSI/Healthcare/Enterprise domains.
- Containerization (Docker, Kubernetes).
- MLOps practices.