AI Solutions Architect

Cicero Group • Salt Lake, WA

19h • Remote

About The Position

About the Role MGT is hiring AI Solutions Architects to join our AI Operating Group (AI OG). The AI OG is responsible for both internal AI tool development and client-facing AI solution delivery, primarily serving the state and local government market. This is a hands-on role. You will design and build AI-powered solutions for real client problems, not write slide decks about what AI could do. You will work across the full lifecycle: discovery, architecture, build, deployment, and iteration. The right person for this role sits comfortably at the intersection of technical capability and business problem-solving. This is not a traditional software engineering position. We need people who can sit in a room with a client, understand their operational challenge, and translate that into a working AI architecture. You should be comfortable with concepts like RAG pipelines, agentic workflows, prompt engineering, and cloud deployment. But your real value is in how you think and solve problems, not just what you can code. What You’ll Do Design end-to-end AI solution architectures for client engagements, from problem discovery through production deployment Build and implement RAG pipelines, agentic workflows, and multi-agent systems using frameworks such as LangChain and LangGraph Architect data pipelines and integration patterns that connect AI capabilities to existing client systems and data sources Work with tool-layer integration standards such as MCP (Model Context Protocol) to connect agents with enterprise systems Develop reusable components, skills, templates, and accelerators that scale across multiple engagements Collaborate with project leads, consultants, and subject matter experts to translate business requirements into technical specifications and solution designs Support internal product development across MGT’s AI tool suite Present technical architectures and solution recommendations to both internal leadership and client stakeholders Participate in discovery sessions and workshops to identify high-impact AI use cases within client organizations Required Qualifications 3–5 years of professional experience; does not have to be in AI, but must demonstrate strong technical problem-solving ability and a track record of building solutions that work Hands-on experience with one or more of the following: LLM-based application development, retrieval-augmented generation (RAG) architectures, agentic design patterns, prompt engineering, or vector databases Demonstrated ability to learn new technical capabilities and platforms quickly Strong communication skills; you will work with consultants, clients, and executive leadership, not just engineers Ability to independently scope, architect, and deliver technical solutions with minimal oversight A builder mentality: you would rather figure it out and ship it than wait for a detailed specification Bachelor’s degree or equivalent practical experience Preferred Qualifications Experience in consulting, professional services, or client-facing technical delivery Background in data architecture, ETL/ELT pipelines, or analytics platforms Programming experience in Python or similar languages Experience working with cloud-based AI services on any major platform What Success Looks Like Within 30 days: You understand our current tool suite, architecture patterns, and active client engagements. You have shipped something. Within 90 days: You are independently architecting solutions for client projects and contributing to internal product development. Within 6 months: You are leading technical delivery on engagements, mentoring team members on AI solution patterns, and shaping our approach to new use cases. Why MGT You will be joining a team that is actively building and shipping AI products, not talking about them. We have real tools in production, real clients using them, and a leadership team that understands both the technology and the business. This is a high-visibility role with direct access to senior leadership and the opportunity to shape how AI gets delivered across the organization. We are building the AI practice from the ground up, which means you will have an outsized impact on the tools, processes, and culture of the team. Our philosophy: clean data foundations first, AI layered on top. Process understanding before automation. Empowering domain experts to build, not centralizing AI capability in a silo. If that resonates with you, this is your team. NOTE: We currently do not accept candidates who require sponsorship, nor are we able to provide sponsorship opportunities to candidates. Positions are available in Salt Lake City, Utah; Washington, D.C.; and remote. Remote employees will be expected to travel to an office periodically.

Requirements

• 3–5 years of professional experience; does not have to be in AI, but must demonstrate strong technical problem-solving ability and a track record of building solutions that work
• Hands-on experience with one or more of the following: LLM-based application development, retrieval-augmented generation (RAG) architectures, agentic design patterns, prompt engineering, or vector databases
• Demonstrated ability to learn new technical capabilities and platforms quickly
• Strong communication skills; you will work with consultants, clients, and executive leadership, not just engineers
• Ability to independently scope, architect, and deliver technical solutions with minimal oversight
• A builder mentality: you would rather figure it out and ship it than wait for a detailed specification
• Bachelor’s degree or equivalent practical experience

Nice To Haves

• Experience in consulting, professional services, or client-facing technical delivery
• Background in data architecture, ETL/ELT pipelines, or analytics platforms
• Programming experience in Python or similar languages
• Experience working with cloud-based AI services on any major platform

Responsibilities

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 11-50 employees