Agentic AI & MCP Specialist

Role Summary

This position involves designing, developing, and operationalizing advanced agentic systems powered by large language models (LLMs) and Model Context Protocol (MCP) frameworks. As a specialist, the focus is on creating intelligent, multistep, tool-using agents capable of autonomous reasoning, planning, and executing complex workflows within cloud-based analytics environments. The role includes technical leadership, system integration, and translating experimental AI architectures into scalable, production-ready solutions.

Responsibilities

• Develop and maintain production-grade applications and services leveraging agentic AI systems, including planning, tool use, and multistep reasoning.
• Design and implement MCP-based integrations, tool interfaces, and model-driven service frameworks.
• Architect and deploy secure, scalable AI applications utilizing cloud-native environments such as Azure, AWS, or GCP.
• Lead solution design efforts, mentor engineering teams, and communicate complex technical concepts to stakeholders.
• Translate ambiguous business or mission requirements into effective AI-driven solutions.
• Incorporate LLM development best practices, including finetuning, prompt engineering, and retrieval-augmented generation (RAG).
• Implement and manage version control, CI/CD pipelines, automated testing, and deployment automation.
• Ensure compliance, security, and governance standards, especially when handling sensitive data.
• Explore emerging agentic patterns, conduct proof-of-concept projects, and evaluate new frameworks and technologies.
• Support monitoring, testing, and optimization of agentic systems to enhance performance and reliability.

Qualifications

• Bachelor''s degree in computer science, software engineering, or a related field.
• 10+ years of professional experience in software development, particularly in building scalable, production applications.
• Proven expertise in developing agentic AI solutions, including planning, tool use, and multistep workflows.
• Hands-on experience with MCP-based integrations, tool interfaces, and model-driven frameworks.
• Proficiency in Python programming, distributed computing, APIs, microservices, and cloud-native architectures.
• Experience deploying AI solutions on cloud platforms such as AWS, Azure, or GCP.
• Strong knowledge of MLOps principles including versioning, deployment automation, and monitoring.
• Ability to interpret complex requirements and develop scalable AI solutions.
• Effective communication skills to collaborate with technical and non-technical teams.
• This position requires eligibility for a U.S. Government security clearance. In accordance with federal law, U.S. citizenship is required.

Publishing Pay Range: $65.00 - $75.00 Hourly

This is a fully remote role and can be performed from an approved location.