Google ADK GenAI Developer

 We are seeking a Google ADK GenAI Developer to join our team in Charlotte, NC (Need Onsite day 1,hybrid 3 days from office)
Job Description:

• Minimum 5+ years of software engineering experience with at least 2+ years focused on Generative AI and Agentic AI development.
• Hands-on experience developing AI applications using Google Agent Development Kit (ADK).
• Strong expertise in Python programming and AI application development.
• Experience working with Google Vertex AI, Gemini Models, AI Studio, and Google Cloud Platform (Google Cloud Platform).
• Hands-on experience building AI Agents, Multi-Agent Systems, and Agentic Workflows.
• Strong knowledge of Retrieval-Augmented Generation (RAG), embeddings, semantic search, and knowledge retrieval systems.
• Experience working with Vector Databases such as Pinecone, Weaviate, Chroma, Milvus, or Vertex AI Vector Search.
• Knowledge of AI orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
• Experience integrating AI solutions with REST APIs, enterprise applications, databases, and third-party services.
• Strong understanding of prompt engineering, model evaluation, and LLM optimization techniques.
• Experience developing and deploying cloud-native applications in Google Cloud Platform environments.
• Knowledge of containerization technologies such as Docker and Kubernetes.
• Experience with CI/CD pipelines and DevOps practices.
• Understanding of AI governance, responsible AI, security, and compliance requirements.
• Experience working in Agile/Scrum environments.
• Strong analytical, debugging, and problem-solving capabilities.
• Excellent communication and stakeholder management skills.
• Banking and Financial Services domain experience is preferred.

• Design and develop enterprise-grade AI agents using Google ADK and Gemini models.
• Build and maintain Agentic AI solutions capable of reasoning, planning, and executing complex business workflows.
• Develop RAG-based applications integrating enterprise knowledge repositories and data sources.
• Implement AI agent orchestration frameworks to support multi-agent collaboration and task execution.
• Integrate AI services with enterprise platforms, APIs, databases, and external applications.
• Create and optimize prompts, tools, and workflows to improve AI agent effectiveness and response quality.
• Collaborate with AI architects and business teams to translate requirements into scalable AI solutions.
• Develop secure and production-ready AI applications following enterprise architecture and governance standards.
• Monitor and optimize AI model performance through evaluation, testing, and continuous improvement.
• Support deployment and operationalization of AI applications within cloud environments.
• Implement observability, security, and compliance controls for AI systems and agent ecosystems.
• Participate actively in Agile ceremonies including sprint planning, backlog refinement, standups, and retrospectives.
• Troubleshoot and resolve AI application issues during development, testing, and production support phases.
• Create technical documentation including architecture diagrams, design specifications, and operational procedures.
• Evaluate emerging AI technologies and frameworks and recommend adoption opportunities.
• Partner with cross-functional teams to ensure successful delivery of AI transformation initiatives.