Gen AI Developer

Gen AI Developer 📍 Location: New York, New York, United States 🏢 Industry: IT Services and IT Consulting 💼 Work Setting: Onsite We are seeking an innovative Generative AI Developer to design, develop, and deploy advanced AI/ML and Generative AI solutions that drive business value and accelerate digital transformation. Are you passionate about Large Language Models, Retrieval-Augmented Generation (RAG), model fine-tuning, and AI application development? This role offers the opportunity to build cutting-edge AI applications, optimize enterprise search capabilities, and integrate intelligent services into scalable business platforms. The ideal candidate has strong expertise in Python, LLMs, machine learning frameworks, vector search technologies, and modern AI orchestration tools. Key Responsibilities Generative AI Development Large Language Model (LLM) Solutions Design, develop, and deploy Generative AI applications. Build and fine-tune large language models for enterprise use cases. Develop conversational AI and intelligent automation solutions. Optimize model performance, scalability, and reliability. Model Fine-Tuning Utilize techniques including: LoRA (Low-Rank Adaptation) QLoRA Parameter-Efficient Fine-Tuning (PEFT) Instruction Tuning Prompt Engineering Foundation Models Work with models from: Hugging Face Open Source LLM Ecosystems Enterprise AI Platforms RAG (Retrieval-Augmented Generation) Solutions Enterprise Knowledge Systems Build RAG-based applications for intelligent knowledge retrieval. Design AI-powered search and question-answering systems. Integrate structured and unstructured enterprise data sources. Improve information discovery and contextual responses. Vector Search & Retrieval Implement semantic search capabilities. Optimize document retrieval pipelines. Enhance relevance and search accuracy. Support embedding-based architectures. AI/ML Engineering Machine Learning Development Develop solutions using: PyTorch TensorFlow Keras Model Training & Optimization Train, evaluate, and deploy machine learning models. Improve model accuracy and inference performance. Monitor and optimize production AI workloads. Conduct experimentation and model validation. MLOps Practices Support model lifecycle management. Implement deployment and monitoring strategies. Improve model governance and maintainability. AI Frameworks & Tools AI Orchestration & Application Development Build AI-powered systems using: LangChain LlamaIndex Hugging Face Vector Databases AI APIs Enterprise AI Integration Integrate AI capabilities into business applications. Develop scalable AI services and APIs. Enable intelligent workflows and automation. Support cloud-based AI deployments. API & Platform Development AI Service Integration Develop APIs supporting AI and machine learning workloads. Expose AI models through secure and scalable services. Integrate AI capabilities into enterprise applications. Scalable Solutions Design high-performance AI architectures. Support distributed inference and model serving. Ensure scalability, reliability, and maintainability. Agile Development & Collaboration Cross-Functional Partnership Collaborate with: Product Managers Software Engineers Data Scientists Machine Learning Engineers Business Stakeholders Requirements Translation Analyze business requirements and technical needs. Convert requirements into AI-powered solutions. Deliver production-ready AI applications. Agile Delivery Participate in Agile ceremonies and sprint planning. Contribute throughout the full software development lifecycle. Support testing, deployment, and continuous improvement. Required Qualifications Education Bachelor's Degree in: Computer Science Artificial Intelligence Data Science Machine Learning Engineering Related Technical Field Experience Generative AI Experience building: Large Language Model (LLM) Applications RAG Systems AI Assistants Enterprise AI Solutions Machine Learning Hands-on experience with: Model Training Fine-Tuning Inference Optimization Production AI Deployments Technical Skills Programming Python API Development AI Service Integration Machine Learning Frameworks PyTorch TensorFlow Keras Generative AI Large Language Models (LLMs) Prompt Engineering Fine-Tuning LoRA QLoRA Hugging Face Transformers RAG & Search LangChain LlamaIndex Semantic Search Vector Search Retrieval-Augmented Generation AI Engineering Model Training Model Optimization MLOps AI Deployment Preferred Skills Vector Databases Embedding Models Cloud AI Platforms NLP Agentic AI Workflows Multi-Agent Systems AI Governance AI Security Distributed AI Systems Key Skills Generative AI LLM RAG Python PyTorch TensorFlow Keras LangChain LlamaIndex Hugging Face LoRA QLoRA Machine Learning NLP API Development Show more Show less