About this opportunity
Compunnel, Inc. lists this Senior GenAl Engineer - Google ADK + Agentic AI opportunity in charlotte, North Carolina. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Senior GenAl Engineer - Google ADK + Agentic AI
Location: North Carolina, Charlotte
Posted: 07/08/2026
Engagement: Contract
Status: Active
Overview
We are seeking a Senior Generative AI Engineer to design, develop, and deploy enterprise-scale Agentic AI and Generative AI solutions. This role is responsible for building production-ready AI applications using Google Agent Development Kit (ADK), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), LangChain, and LangGraph while driving AI platform strategy, engineering standards, and operational excellence. The ideal candidate will have strong software engineering expertise, experience building AI-enabled enterprise applications, and a deep understanding of modern agentic architectures.
Responsibilities
Design, develop, and deploy production-ready AI agents using Google Agent Development Kit (ADK).
Build multi-agent AI solutions leveraging Google ADK orchestration, tool ecosystems, and deployment frameworks.
Design and develop Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic architectures.
Build production-grade AI workflows using LangChain and LangGraph.
Develop AI-enabled services and integrate AI capabilities into enterprise applications and business workflows.
Design secure tool execution patterns supporting service-to-service communication, least privilege access, auditability, and enterprise governance.
Implement enterprise agent-to-agent communication patterns and Model Context Protocol (MCP) tool integrations where applicable.
Evaluate AI technologies, orchestration frameworks, and model architectures to address complex business requirements.
Troubleshoot, optimize, and resolve issues across AI models, orchestration frameworks, and production services.
Develop AI lifecycle capabilities including evaluation frameworks, quality monitoring, model performance tracking, and model drift detection.
Design, code, test, debug, document, and deploy AI services across development, testing, and production environments.
Contribute to enterprise AI platform strategy, engineering standards, and operational readiness initiatives.
Collaborate with architects, engineers, product teams, and business stakeholders to deliver scalable AI solutions.
Mentor engineers, provide technical leadership, and serve as an escalation point for complex technical challenges.
Ensure AI solutions comply with organizational security, governance, compliance, and risk management standards.
Required Qualifications
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field, or equivalent practical experience.
Strong hands-on experience developing enterprise applications using Python and/or Java.
Strong understanding of Large Language Models (LLMs), transformer architectures, and conversational AI.
Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
Hands-on experience with LangChain and LangGraph frameworks.
Experience building and deploying production-grade Agentic AI applications.
Experience implementing Model Context Protocol (MCP) integrations and enterprise AI orchestration patterns.
Experience with MLOps practices, AI model evaluation, quality monitoring, and model lifecycle management.
Experience building and managing vector databases for semantic search and knowledge retrieval.
Experience implementing vector search, embeddings, and enterprise retrieval architectures.
Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Experience with containerized application deployment and cloud-native architectures.
Experience implementing CI/CD pipelines and automated software deployment processes.
Strong analytical, debugging, troubleshooting, and problem-solving skills.
Excellent verbal and written communication skills with the ability to explain complex AI concepts to technical and business stakeholders.
Preferred Qualifications
Experience implementing human-in-the-loop workflows, policy guardrails, and AI safety controls for agentic systems.
Experience with event streaming and messaging technologies such as Apache Kafka.
Experience with Test-Driven Development (TDD), Behavior-Driven Development (BDD), and modern software engineering practices.
Experience working in financial services or other regulated industries.
Experience designing enterprise AI governance, monitoring, and operational frameworks.
Experience leading AI engineering teams and mentoring software engineers.
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Worksite address
charlotte, NC, 28245, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.