Job Title: SR Gen AI Engineer
Location: NYC, NY (Onsite)
Duration: 12 Months + Extension
Bill Rate: $94/hr
Job Type: W2 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
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.
Key Responsibilities:
- 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.
Required Skills:
- 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.
Equal opportunity employer: We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
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