Agentic AI Engineer

Role Description

Own your opportunity to shape the future of AI at GDIT. As an Agentic AI Engineer supporting the mission of the United States Postal Service (USPS), you will design, develop, and deploy AI solutions that modernize and optimize essential nationwide operations. Your work will directly contribute to improved efficiency, automated processes, and data‑driven decision making across a high‑impact federal environment.

MEANINGFUL WORK & PERSONAL IMPACT

• Play a critical role in identifying where AI can streamline business processes and deliver measurable outcomes across USPS.
• Support may include expertise in AI strategy, generative AI, machine learning, large language models, agentic AI, automation, analytics, governance, software engineering, architecture, and enterprise operational support.

Agentic AI & Architecture

• Design and develop autonomous AI agents capable of reasoning, planning, and executing multi‑step workflows.
• Create agent‑based architectures using orchestration frameworks such as LangChain, AutoGen, and similar technologies.
• Build modular APIs, integrations, tools, and memory management capabilities, including vector database integration, to support intelligent agent operations.
• Integrate AI solutions with existing enterprise automation frameworks to reduce manual effort and enhance operational quality.
• Identify opportunities for AI‑enabled automation, operational efficiencies, productivity improvements, and modernization across USPS workflows.

ML/LLM Engineering

• Demonstrate ability to design, build, train, deploy, integrate, and maintain machine learning and LLM‑based solutions.
• Develop AI‑enabled automation solutions that improve business processes and support SDLC activities including coding, testing, debugging, deployment, and operational support.
• Build tools that automate requirements and test case generation using Visual Studio Code, Python, Microsoft Copilot, CrewAI, or other USPS‑approved platforms.
• Provide actionable recommendations, solution strategies, and operational insights to improve organizational performance and mission outcomes.

MLOps, Platforms & Performance

• Implement MLOps practices, CI/CD pipelines, containerization technologies, and scalable deployment environments to support enterprise AI operations.
• Establish evaluation and testing pipelines to measure AI accuracy, reliability, performance, scalability, and operational effectiveness.
• Provide deep AI technical expertise to troubleshoot, diagnose, optimize, and maintain advanced AI systems, machine learning models, and production AI environments.
• Optimize AI model performance, scalability, efficiency, and accuracy using tools such as PyTorch and TensorFlow.

Data & Analytics

• Ensure data quality, integrity, governance, and security for AI model training, evaluation, deployment, and sustainment.
• Support the collection, preprocessing, analysis, visualization, and reporting of large-scale structured and unstructured datasets.
• Develop dashboards, reports, predictive analytics, and executive‑level visualizations to support decision‑making and operational planning.

Governance, Risk & Compliance

• Develop and implement AI governance frameworks, policies, security controls, ethical AI standards, transparency mechanisms, and compliance processes.
• Ensure compliance with cybersecurity, privacy, regulatory, and organizational requirements applicable to AI systems and enterprise environments.
• Monitor, assess, and mitigate risks associated with AI deployment, automation, and enterprise integration.
• Support executive leadership with AI strategic advisory services, roadmap development, assessments, briefings, and stakeholder engagement.

Collaboration, Enablement & Mission Outcomes

• Evaluate opportunities to embed AI across enterprise workflows and design solutions aligned with USPS mission needs.
• Collaborate with CIO leadership, technical teams, program offices, and business stakeholders to support AI adoption, integration, and enterprise modernization.
• Translate technical AI concepts into business‑focused recommendations and operational outcomes.
• Provide technical training, mentoring, workshops, documentation, and knowledge transfer to support workforce readiness and sustainability.
• Train designated team members to maintain and operate AI‑driven tools and scripts.
• Support continuous improvement initiatives related to AI performance, governance, operational effectiveness, emerging technologies, and enterprise AI adoption.
• Provide ongoing operational and technical support for deployed AI capabilities, including monitoring, maintenance, troubleshooting, optimization, retraining, and lifecycle management.

Qualifications

• Bachelor’s degree in a related field with strong mathematics; or an additional four years of relevant professional experience in lieu of a degree.
• 5+ years of hands‑on AI development experience for Senior AI Engineer.
• 8+ years of experience leading or delivering AI, automation, or software development projects for Principal AI Engineer.
• Proven experience contributing to or leading AI/automation initiatives.
• Experience in analytics, data‑driven environments, or team leadership roles is highly desirable.
• Strong agentic AI experience with agent frameworks, orchestration tools, and automation workflows.
• Strong mathematical foundation in algebra, statistics, calculus, or related fields applied to AI/ML model development.
• Hands‑on experience developing, training, and evaluating AI/ML models.
• Experience optimizing model performance, scalability, or efficiency.
• Practical experience applying machine learning to real‑world business or operational challenges.

Requirements

• Proficiency building AI solutions using Python, Visual Studio Code, and related languages.
• Strong understanding of generative AI, LLM integration, and modern AI frameworks.
• Ability to develop AI‑driven tools that convert business user stories into technical requirements.
• Experience integrating AI capabilities into enterprise automation frameworks, applications, and systems using APIs, microservices, cloud technologies, and scalable deployment strategies.
• Ability to deliver AI scripts and programs that run reliably on USPS‑approved environments.
• Capability to document, train, and transition AI tools to operational teams.
• Experience with LangChain, AutoGen, and related orchestration frameworks.
• Experience with vector databases and memory management techniques.
• Experience with PyTorch and TensorFlow.
• Experience implementing MLOps, CI/CD, containerization, and observability/monitoring.

Benefits

• Comprehensive benefits and wellness packages.
• 401K with company match.
• Competitive pay and paid time off.
• Full flex work weeks where possible.
• 15 days of paid leave per calendar year for vacations, personal business, and illness.
• 10 paid holidays per year.
• Paid Family Leave program providing up to 160 hours of paid leave in a rolling 12 month period for eligible employees.
• Short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance.