eSimplicity is seeking a Principal AI Engineer (Agentic AI & MCP Specialist) to architect, develop, and operationalize next-generation agentic systems powered by large language models and Model Context Protocol frameworks. This role focuses on building intelligent, multi-step, tool-using agents that can autonomously reason, plan, and execute complex workflows across a cloud-based analytics ecosystem. You will design and implement agent orchestration frameworks, integrate model-driven decision logic, and deliver production-grade AI capabilities that safely leverage emerging AI techniques. The ideal candidate combines strong software engineering fundamentals with hands-on experience in agentic systems, MCP integrations, LLM-driven tooling, and secure, scalable AI applications. Responsibilities include technical leadership, exploring cutting-edge agentic patterns, driving proof-of-concept innovation, and partnering with engineering and product teams to translate experiments into real-world impact. Requirements include U.S. citizenship or eligibility for public trust clearance, a bachelor's degree and 10+ years of software engineering experience, experience designing and deploying production applications and agentic AI solutions, MCP integrations, tool interfaces, and cloud deployments (Azure, AWS, or GCP). Proficiency in Python, APIs, microservices, distributed computing, and cloud-native architectures; familiarity with MLOps and LLMOps practices; ability to communicate AI concepts to technical and non-technical audiences; and experience with version control, testing, and depl

eSimplicity is seeking a Principal AI Engineer (Agentic AI & MCP Specialist) to architect, develop, and operationalize next-generation agentic systems powered by large language models and Model Context Protocol frameworks. This role focuses on building intelligent, multi-step, tool-using agents that can autonomously reason, plan, and execute complex workflows across a cloud-based analytics ecosystem. You will design and implement agent orchestration frameworks, integrate model-driven decision logic, and deliver production-grade AI capabilities that safely leverage emerging AI techniques. The ideal candidate combines strong software engineering fundamentals with hands-on experience in agentic systems, MCP integrations, LLM-driven tooling, and secure, scalable AI applications. Responsibilities include technical leadership, exploring cutting-edge agentic patterns, driving proof-of-concept innovation, and partnering with engineering and product teams to translate experiments into real-world impact. Requirements include U.S. citizenship or eligibility for public trust clearance, a bachelor's degree and 10+ years of software engineering experience, experience designing and deploying production applications and agentic AI solutions, MCP integrations, tool interfaces, and cloud deployments (Azure, AWS, or GCP). Proficiency in Python, APIs, microservices, distributed computing, and cloud-native architectures; familiarity with MLOps and LLMOps practices; ability to communicate AI concepts to technical and non-technical audiences; and experience with version control, testing, and depl