Principal AI Engineer

This is a fully remote position, open to applicants in Maryland.

📋 Description

• The Agentic AI & MCP Specialist will be responsible for designing, developing, and operationalizing cutting-edge agentic systems that utilize advanced LLMs and Model Context Protocol (MCP) frameworks.

• This position emphasizes the creation of intelligent, multi-step, tool-utilizing agents capable of autonomously reasoning, planning, and executing intricate workflows within a cloud-based analytics environment.

• The specialist will be tasked with formulating and implementing agent orchestration frameworks, integrating model-driven decision logic, and building resilient, production-quality agent capabilities that effectively leverage emerging AI methodologies.

• This role demands a highly skilled software developer who merges strong engineering principles with practical experience in constructing agentic systems, engaging with MCP-based integrations, designing LLM-driven tools, and developing secure, scalable AI applications.

• The position offers technical leadership, investigates innovative agentic patterns, propels proof-of-concept advancements, and collaborates with engineering and product teams to translate experimental architectures into tangible outcomes.

⛳️ Requirements

• All applicants must obtain public trust clearance from the U.S. Federal Government.

• A Bachelor’s Degree along with over 10 years of software engineering experience is required.

• Proven experience in designing, developing, and supporting production applications, platforms, or services is essential.

• Experience in developing agentic AI solutions, which includes planning, tool usage, workflow orchestration, multi-step reasoning, or autonomous task execution, is necessary.

• Experience in designing and implementing Model Context Protocol (MCP) integrations, tool interfaces, or model-driven service architectures is required.

• Candidates must be able to analyze business, customer, or mission requirements and create scalable AI-driven solutions that align with both technical and operational goals.

• Familiarity with large language model (LLM) development practices, such as fine-tuning, retrieval-augmented generation (RAG), prompt engineering, and agent interaction patterns is preferred.

• Proficiency in Python, along with experience working with APIs, microservices, distributed computing environments, and cloud-native architectures, is necessary.

• Experience in deploying and integrating AI agents or LLM-enabled applications within cloud platforms like Azure, AWS, or Google Cloud Platform (GCP) is required.

• Knowledge of MLOps and LLMOps practices, including model versioning, automated testing, deployment automation, monitoring, performance evaluation, and governance is essential.

• Ability to engage in solution design discussions, provide technical guidance to team members, and convey AI-related concepts to both technical and non-technical audiences is important.

• Experience utilizing version control systems and CI/CD practices, including source code management, automated testing, deployment pipelines, and release management for production settings is required.

🏝️ Benefits

• Medical, dental, and vision coverage

• 401(k) retirement benefits

• Paid time off

• Paid holidays

• Life and disability insurance

• Additional wellness and employee support programs