AI Solutions Architect

DC Office

1015 15th St NW

6th Floor

Washington, DC 20005, USA

DC Office

1015 15th St NW

6th Floor

Washington, DC 20005, USA

Job Title: AI Solutions Architect
FLSA Status:
Exempt
Full-Time
Location:
Salt Lake City, UT;
Washington, DC; or Remote

WHO WE ARE:

MGT is a leading provider of technology and advisory solutions serving state, local, and education government agencies (SLED) across the United States. Through client partnerships, MGT’s almost 1,200 employees impact communities for good by managing and securing critical networks, solving complex human capital and fiscal problems, elevating education systems, and advancing equity as a performance imperative. MGT partners with thousands of agencies as a trusted advisor delivering solutions that improve technology, operational, and economic performance to help communities thrive.

Founded in 1975, MGT initiated an ambitious restart in 2016, broadening the solutions portfolio to provide the most specialized solutions, tackling the most mission‑critical problems that live at the top of the public agency leadership agenda. MGT drives over 20% compound annual organic growth and utilizes programmatic mergers and acquisitions to grow capabilities, attract top talent, and accelerate growth scale. Since 2020, MGT has successfully completed 13 acquisitions, driving over 60% compound annual inorganic growth.

Celebrating its 50th year in 2025, the firm attracts exceptional talent and empowers them to exceed client expectations as they navigate the dynamic demands of the clients we serve. Hear more about MGT’s culture in the words of our employees .

WHAT YOU’LL DO:

The AI Solutions Architect will join MGT’s AI Operating Group (AI OG), which is responsible for internal AI tool development and client‑facing AI solution delivery, primarily for state and local government clients. This is a hands‑on consulting and building role focused on designing and delivering AI‑powered solutions for real client problems across discovery, architecture, build, deployment, and iteration. In this role, you will:

• Design end-to-end AI solution architectures for client engagements, from problem discovery through production deployment.
• Build and implement retrieval‑augmented generation (RAG) pipelines, agentic workflows, and multi‑agent systems using frameworks such as Lang Chain and Lang Graph.
• Architect data pipelines and integration patterns that connect AI capabilities to existing client systems and data sources.
• Work with tool‑layer integration standards, including Model Context Protocol (MCP), to connect agents with enterprise systems.
• Develop reusable components, skills, templates, and accelerators that can scale across multiple engagements.
• Collaborate with project leads, consultants, and subject matter experts to translate business requirements into technical specifications and solution designs.
• Present technical architectures and solution recommendations to internal leadership and client stakeholders.
• Participate in discovery sessions and workshops to identify high‑impact AI use cases within client organizations.

WHAT YOU’LL BRING:

• Hands‑on experience with one or more of the following: LLM‑based application development, retrieval‑augmented generation architectures, agentic design patterns, prompt engineering, or vector databases.
• Strong technical problem‑solving ability and a track record of building practical solutions that work in real operating environments.
• Comfort working at the intersection of consulting and building, including the ability to sit with a client, understand an operational challenge and translate it into a working AI architecture.
• Ability to learn new technical capabilities, platforms, frameworks, and deployment patterns quickly.
• Strong communication skills with the ability to work effectively with consultants, clients, executive leadership, and technical teams.
• Ability to independently scope, architect, and deliver technical solutions with minimal oversight.
• A builder mentality, with a bias toward figuring things out, shipping solutions, and iterating based on feedback.
• Comfort with concepts such as RAG pipelines, agentic workflows, prompt engineering, cloud deployment, and AI…