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

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