Principal AI Engineer

Description About Us: eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow. Responsibilities: The Agentic AI & MCP Specialist will architect, develop, and operationalize next-generation agentic systems powered by advanced LLMs and Model Context Protocol (MCP) 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. The specialist will design and implement agent orchestration frameworks, integrate model-driven decision logic, and build robust, production-grade agent capabilities that safely leverage emerging AI techniques. This position requires a deeply skilled software developer who combines strong engineering fundamentals with hands-on experience creating agentic systems, working with MCP-based integrations, designing LLM-driven tools, and building secure, scalable AI applications. The role provides technical leadership, explores cutting-edge agentic patterns, drives proof-of-concept innovation, and partners with engineering and product teams to translate experimental architectures into real-world impact. Requirements Required Qualifications: All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation. Bachelor’s Degree and 10+ years of software engineering experience Experience designing, developing, and supporting production applications, platforms, or services. Experience developing agentic AI solutions, including planning, tool utilization, workflow orchestration, multi-step reasoning, or autonomous task execution. Experience designing and implementing Model Context Protocol (MCP) integrations, tool interfaces, or model-driven service architectures. Ability to analyze business, customer, or mission requirements and develop scalable AI-driven solutions that align with technical and operational objectives. Experience with large language model (LLM) development practices, including fine-tuning, retrieval-augmented generation (RAG), prompt engineering, and agent interaction patterns. Proficiency in Python and experience working with APIs, microservices, distributed computing environments, and cloud-native architectures. Experience deploying and integrating AI agents or LLM-enabled applications within cloud environments such as 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. Ability to contribute to solution design discussions, provide technical guidance to team members, and communicate AI-related concepts to technical and non-technical audiences. Experience using version control systems and CI/CD practices, including source code management, automated testing, deployment pipelines, and release management for production environments. Desired Qualifications: Experience building multi-agent systems, agent swarms, or coordinated reasoning frameworks. Familiarity with advanced tool-calling strategies, including dynamic tool selection, function-call planning, or graph-structured task planners. Experience with structured LLM evaluation methods, agent benchmarking, or test harnesses for autonomous systems. Knowledge of performance optimization techniques for LLMs and agents, including caching, model distillation, model routing, or accelerated inference. Background integrating agentic components with large-scale data or analytics platforms (e.g., Databricks, Snowflake, Spark). Hands-on experience developing innovative POCs or experimental agentic architectures in fast-paced R&D environments. Familiarity with emerging agentic frameworks such as Strands Agents, LangGraph, CrewAI, etc. Exposure to safety-oriented design patterns for autonomous systems, including guardrails, validation layers, or constrained-action frameworks. Experience designing and building secure, compliance-aware systems that handle sensitive data in accordance with HIPAA and federal security standards, including implementation of encryption, access controls, auditability, and governance for protected health information (PHI) within AI/LLM workflows. Working Environment : eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by manager. Occasional travel for training and project meetings. It is estimated to be less than 5% per year. Benefits: eSimplicity offers a comprehensive benefits package, including medical, dental, and vision coverage, 401(k) retirement benefits, paid time off, paid holidays, life and disability insurance, and additional wellness and employee support programs. Eligibility may vary based on employment status and applicable plan terms. Reasonable Accommodation: eSimplicity is committed to providing reasonable accommodations to qualified individuals with disabilities during the application and hiring process. Applicants who need assistance or an accommodation should contact Human Resources. Equal Employment Opportunity: eSimplicity is an Equal Opportunity Employer, including disability and protected veteran status. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability, or any othe