Senior GenAi Developer

Job Title: Senior GenAI Developer Location: Atlanta, GA Employment Type: W2 Only Visa Status: H1B Only Experience: 12+ Years Job Summary: We are seeking a highly experienced Senior GenAI Developer with 12+ years of overall IT experience and deep expertise in Generative AI, Large Language Models (LLMs), and AI-driven application development. The ideal candidate will lead the design, development, and deployment of scalable GenAI solutions, integrating them into enterprise systems while ensuring security, performance, and reliability. Key Responsibilities: Design, develop, and deploy Generative AI applications using LLMs for text, code, image, and conversational use cases Architect and implement end-to-end GenAI pipelines, including data ingestion, embeddings, vector storage, and inference Build and optimize prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning, and model evaluation workflows Integrate GenAI solutions with enterprise applications, APIs, and microservices Develop AI agents, chatbots, copilots, and automation solutions using GenAI frameworks Ensure AI solutions comply with security, privacy, and responsible AI guidelines Optimize model performance, latency, scalability, and cost in production environments Collaborate with data scientists, product managers, and business stakeholders Mentor junior engineers and provide technical leadership across GenAI initiatives Stay current with advancements in LLMs, multimodal models, and AI tooling Required Skills & Qualifications: 12+ years of overall IT experience with strong hands-on development background 5+ years of experience in AI/ML, with recent focus on Generative AI Strong proficiency in Python (mandatory); experience with Java or Node.js is a plus Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.) Expertise in Prompt Engineering, RAG, vector databases (Pinecone, FAISS, Weaviate, Chroma) Experience with LangChain, LlamaIndex, Semantic Kernel, or similar frameworks Strong knowledge of REST APIs, microservices, and cloud-native architectures Experience deploying AI solutions on AWS / Azure / GCP Knowledge of Docker, Kubernetes, CI/CD pipelines Strong understanding of data security, governance, and ethical AI practices