AI Solutions Architect

Overview

The AI Solutions Architect is an experienced, hands-on builder, consultant, and enabler — embedded with MRO’s business units to deliver white-glove AI enablement, bespoke workflow engineering, solution consulting, and training. The role pairs direct, roll-up-your-sleeves delivery in assigned business areas with curation of the AI capabilities and context layer (prompt libraries, skills, resource libraries, and workflows) that amplify team effectiveness across the entire org.  

The AI Solutions Architect will dive in with rapid, full-stack prototyping of internal tools to boost productivity – and therefore must be product-minded, outcome oriented, and comfortable coordinating with multidisciplinary stakeholders. They also serve as an internal and external thought leader on AI in healthcare and support principal leadership with AI strategy, planning, and coordination across the AI Domain. 

Responsibilities

• Deliver white-glove AI enablement, consulting, and solution engineering across assigned business units: tool setup, training, workflow configuration, and ongoing support. 
• Build bespoke AI workflows, agents, and full-stack lightweight internal tools, tailored to each assigned area’s specific needs. 
• Provide solution consulting: assess team workflows, identify AI opportunities, and scope and deliver improvements. 
• Curate MRO prompt libraries, skill repositories, and other agent context — the content/curation layer — in partnership with Principal Architects and Engineers  
• Design and deliver role-specific AI training and coaching for assigned populations, including focused enablement for senior leaders. 
• Create and maintain playbooks, documentation, and the knowledge base for AI tools and workflows in assigned areas. 
• Gather and synthesize feedback on AI adoption barriers and report insights to leadership. 
• Develop customer-facing thought leadership: posts, articles, and conference presentations on AI in healthcare. 
• Support principal leadership on AI strategy, planning, team coordination, and R&D methodology across the AI Domain’s product-aligned teams. 

Qualifications

Required: 

• Demonstrated depth in applied AI: hands-on experience building LLM-based applications, agents, and prompt engineering at scale, including running statistical or structured evaluations of AI outputs. 
• Proficient with AI and agentic coding and development tools (Claude Code, OpenAI Codex, Github Copilot)  
• Strong software-engineering or technical foundation, including proficiency in Python and familiarity with at least one major cloud AI platform (GCP Vertex AI, Azure AI, or AWS Bedrock). 
• Experience with Healthcare IT, HIPAA guardrails, and responsible-AI. 
• Demonstrated initiative and self-direction in AI (self-directed learning, side projects, internal AI experiments); often the recognized go-to person for AI questions in their current team. 
• Excellent communication skills for consulting, training, documentation, and cross-team stakeholder engagement. 
• Patient, consultative, “let’s figure this out together”, optimistic team player 

Preferred: 

• Experience with clinical data workflows, especially with FHIR and EHR integrations. 
• Strong understanding of MRO’s business lines, systems, and stakeholder landscape in one or more business areas   
• Experience with C# / .NET; Ruby on Rails; and/or Python  
• Familiarity with containerized microservice architectures and CI/CD pipelines. 
• Background in technology consulting, enablement, training delivery, or internal center-of-excellence models. 
• Published technical content or open-source AI contributions. 

Total CompensationBase pay is one element of the total compensation package. Eligible employees may also receive an annual cash bonus and have access to a comprehensive benefits offering, including medical, dental, vision, life insurance, and a 401(k) plan.

Salary Range It is not typical for an individual to be hired at or near the top of the range. Individual pay may be influenced by factors such as skills, qualifications, experience, licensure, certifications, geographic location, and internal equity.

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