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Senior GenAI Engineer: Enterprise Agentic AI
Compunnel
6 hours ago
Full-time
On-site
Charlotte, North Carolina, United States
Senior GenAl Engineer - Google ADK + Agentic AI
North Carolina, Charlotte 07/08/2026 Contract Active Job Description:
Job Summary 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. Key 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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North Carolina, Charlotte 07/08/2026 Contract Active Job Description:
Job Summary 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. Key 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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