Senior GenAI Developer/Lead

Role: Senior GenAI Developer/Lead Agentic AI & RAG SolutionsWork Location: NY -10004 & Alpharetta GA (Onsite/Hybrid, 3 days from office)Interviews Mode: 1 virtual technical interview and 1 Final client In-person interview Role SummaryWe are seeking a highly skilled Senior GenAI Developer with strong expertise in Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. The ideal candidate will design, develop, and deploy AI-powered applications leveraging Large Language Models (LLMs), intelligent agents, vector databases, and cloud-native AI services. This role requires hands-on experience building scalable AI solutions that automate business processes and deliver advanced conversational experiences.Key Responsibilities

• Design and develop GenAI applications using LLMs, RAG architectures, and Agentic AI frameworks.
• Build intelligent AI agents capable of planning, reasoning, tool usage, and multi-step task execution.
• Develop and optimize RAG pipelines using vector databases and embedding models.
• Integrate OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs into enterprise applications.
• Create AI-powered chatbots, copilots, virtual assistants, and workflow automation solutions.
• Fine-tune prompts, evaluate model performance, and improve response quality.
• Implement orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
• Develop scalable APIs and backend services using Python.
• Collaborate with data engineers, architects, and business stakeholders to deliver AI-driven solutions.
• Ensure AI security, governance, observability, and responsible AI practices.

Required Skills

• Strong experience in Generative AI and Large Language Models (LLMs).
• Hands-on expertise with RAG (Retrieval-Augmented Generation) architecture.
• Strong experience in Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, or Semantic Kernel.
• Advanced programming skills in Python.
• Experience with vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, or Milvus.
• Strong understanding of embeddings, prompt engineering, and model evaluation.
• Experience integrating LLMs through APIs and cloud platforms.
• Knowledge of REST APIs, Microservices, and scalable backend development.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Preferred Skills

• Experience with Azure OpenAI Services.
• Exposure to fine-tuning, model training, and MLOps.
• Experience with knowledge graphs and multi-agent systems.
• Familiarity with Kubernetes, Docker, and CI/CD pipelines.
• Experience building AI applications for Banking, Financial Services, or Enterprise domains.

TechnologiesGenAI: OpenAI, Azure OpenAI, Claude, Gemini, Llama

Frameworks: LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel

Programming: Python, FastAPI, REST APIs

Data: Vector Databases, SQL/NoSQL Databases

Cloud: AWS, Azure, Google Cloud Platform