Principal AI Engineer

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

📋 Description

• Design, develop, and operationalize state-of-the-art agentic systems utilizing advanced LLMs and MCP frameworks.

• Create intelligent, multi-step, tool-using agents capable of autonomous reasoning, planning, and executing intricate workflows.

• Conceptualize and implement frameworks for agent orchestration.

• Integrate decision logic driven by models.

• Develop robust, production-quality agent capabilities employing emerging AI techniques.

• Provide technical leadership and investigate cutting-edge agentic methodologies.

• Propel innovation through proof-of-concept initiatives.

• Collaborate with engineering and product teams to convert experimental architectures into tangible outcomes.

• Operate within a cloud-based analytics environment.

• Engage with government clients during Eastern time zone hours.

• Participate in occasional training and project meetings.

⛳️ Requirements

• Must successfully obtain public trust clearance from the U.S. Federal Government.

• Must be a U.S. citizen or obtain clearance through the Foreign National Government System.

• For foreign nationals: must have resided in the United States for at least 3 of the last 5 years.

• Hold a valid, non-expired passport from the country of birth along with the necessary visa/work permit documentation.

• Bachelor’s Degree required.

• Over 10 years of experience in software engineering.

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

• Experience in developing agentic AI solutions, which include planning, tool utilization, workflow orchestration, multi-step reasoning, or executing tasks autonomously.

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

• Ability to analyze business, customer, or mission requirements and create scalable AI-driven solutions.

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

• Proficient in Python programming.

• Experience with APIs, microservices, distributed computing environments, and cloud-native architectures.

• Involved in deploying and integrating AI agents or LLM-enabled applications in Azure, AWS, or Google Cloud Platform (GCP).

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

• Capable of contributing to solution design discussions and providing technical direction.

• Proficient in communicating AI-related concepts to both technical and non-technical audiences.

• Experience with version control systems and CI/CD practices, including source code management, automated testing, deployment pipelines, and release management.

• Preferred: Experience in building multi-agent systems, agent swarms, or coordinated reasoning frameworks.

• Preferred: Familiarity with advanced tool-calling strategies.

• Preferred: Experience with structured LLM evaluation, agent benchmarking, or autonomous-system test harnesses.

• Preferred: Knowledge of LLM and agent performance optimization.

• Preferred: Experience integrating agentic components with Databricks, Snowflake, Spark, or similar platforms.

• Preferred: Hands-on experience in developing innovative POCs or experimental agentic architectures.

• Preferred: Familiarity with Strands Agents, LangGraph, CrewAI, or analogous frameworks.

• Preferred: Exposure to safety-oriented design patterns such as guardrails and validation layers.

• Preferred: Experience in designing secure, compliance-aware systems that manage sensitive data under HIPAA and federal security standards.

• Preferred: Experience implementing encryption, access controls, auditability, and governance for PHI in AI/LLM workflows.

🏝️ Benefits

• Medical coverage.

• Dental coverage.

• Vision coverage.

• 401(k) retirement benefits.

• Paid time off.

• Paid holidays.

• Life insurance.

• Disability insurance.

• Wellness programs.

• Employee support programs.

• Remote work environment.

• Occasional travel estimated at less than 5% per year.