GenAI Developer (with Google ADK exp)

Role: Google ADK GenAI Developer

Location: Charlotte, NC

Overview

We are seeking a highly skilled Google ADK GenAI Developer with 12+ years of experience in software engineering, AI/ML application development, and cloud technologies. The ideal candidate will have hands-on expertise in Google Agent Development Kit (ADK), Google Gemini, Vertex AI, and enterprise-grade AI agent development. This role involves designing and building scalable GenAI and multi-agent solutions that drive business transformation.

Responsibilities

• Design, develop, and deploy AI agents and multi-agent systems using Google ADK.
• Build enterprise GenAI applications leveraging Gemini models, Vertex AI, prompt engineering, and RAG architectures.
• Develop agent workflows, tool integrations, function calling, and autonomous decision-making capabilities.
• Implement Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.
• Integrate AI agents with enterprise applications, APIs, databases, and cloud services.
• Establish AI governance, security, observability, and monitoring frameworks.
• Optimize LLM performance, latency, scalability, and cost efficiency.
• Collaborate with architects, product owners, data engineers, and business stakeholders to define AI-driven solutions.
• Lead technical design discussions and mentor development teams on GenAI best practices.

Required Skills

• 12+ years of software development experience with strong expertise in Python.
• Hands-on experience with Google Agent Development Kit (ADK).
• Strong experience with Google Gemini, Vertex AI, Agentic AI, and LLM-based applications.
• Expertise in Prompt Engineering, RAG, AI Agents, Multi-Agent Systems, and Tool Calling.
• Experience with LangChain, LangGraph, MCP, AutoGen, or similar agent frameworks.
• Proficiency with Vector Databases such as Pinecone, Weaviate, Chroma, or Vertex AI Vector Search.
• Strong understanding of REST APIs, microservices, and event-driven architectures.
• Experience with Google Cloud Platform (Google Cloud Platform) services.
• Knowledge of Docker, Kubernetes, CI/CD pipelines, and cloud-native development.
• Experience with SQL/NoSQL databases and enterprise integration patterns.

Preferred Skills

• Experience with AgentOps, LLM evaluation, and observability tools.
• Knowledge of MLOps and AI model deployment frameworks.
• Experience with AI governance, responsible AI, and security controls.
• Google Cloud certifications.
• Experience working in Banking, Financial Services, Healthcare, or large enterprise environments.

Nice to Have

• Experience with Devin AI, Claude Code, GitHub Copilot, or AI-assisted software development tools.
• Knowledge of graph databases (Neo4j), knowledge graphs, and advanced reasoning frameworks.
• Exposure to multimodal AI applications and AI-driven workflow automation.