AI Solutions Architect

PAR Technology

1d • $140,000 - $160,000

About The Position

PAR Technology’s AI Enablement & Transformation team delivers governed AI solutions that improve how internal business teams work across HR, Finance, Legal, Operations, Customer Success, Marketing, Sales and Support. This is a hands-on AI solution architecture and delivery role: the architect turns ambiguous business needs into practical technical approaches, builds and launches solutions using PAR-approved AI platforms, and remains accountable for their performance after release. The role partners closely with IT and Enterprise Systems as solutions move into formal production pathways.

The position focuses on determining what should be built, selecting the right approach, creating the solution and ensuring it works reliably after launch. It is not primarily a data analyst, reporting, traditional SaaS product-development, integration-engineering or MCP-development role. The architect will also support AI economics and token optimization by evaluating model choice, usage patterns, solution design, cost and business value across PAR’s AI tooling investments.

The role owns solution architecture and delivery, post-production performance and improvement, collaboration with IT and Enterprise Systems, intake and portfolio management, AI economics and platform evaluation, and governance and quality. Success means delivering useful, reliable and governed AI solutions; establishing reusable patterns and clear ownership; supporting future production scale; and managing platform and token costs through sound architecture and model choices.

Requirements

• Demonstrated experience designing and delivering AI-powered solutions, agents, automations or internal tools used by real business teams.
• Strong solution architecture judgment, including the ability to turn an unclear business problem into a practical technical design, delivery plan and working solution.
• Hands-on experience with enterprise AI platforms such as Claude Enterprise, Microsoft Copilot, Copilot Studio, Azure AI or comparable tools.
• Ability to build and configure AI solutions using system instructions, knowledge sources, tool use, workflow logic, structured outputs and appropriate human review.
• Ability to assess whether a need is best addressed through platform configuration, an agent, workflow automation, a lightweight application, an integration or no build.
• Experience taking prototypes beyond demonstration quality, including testing, permissions, documentation, monitoring, support planning and iterative improvement.
• Working knowledge of APIs, MCP, webhooks and enterprise integration patterns sufficient to evaluate and guide their use; deep integration engineering is not the primary focus.
• Familiarity with Microsoft 365, SharePoint and Azure environments.
• Ability to explain technical decisions, risks and tradeoffs to non-technical business leaders.
• Strong prioritization and delivery management skills, including the ability to own an intake queue without becoming only an intake coordinator.
• Candidates should be prepared to discuss two AI solutions they personally designed and delivered, including the business problem, approach, personal contributions, testing, post-launch results and changes made when performance was not as expected.

Nice To Haves

• Experience delivering internal AI solutions across multiple corporate functions in a SaaS or complex enterprise environment.
• Experience partnering with IT, Enterprise Systems, Security, Legal or enterprise architecture teams.
• Experience using AI-assisted development tools to accelerate solution delivery while maintaining quality, security and maintainability standards.
• Familiarity with AI governance, data classification, access controls and audit requirements.
• Experience measuring adoption, productivity impact, solution quality and cost after launch.

Responsibilities

• Translate business problems, workflows, constraints and desired outcomes into clear AI solution designs.
• Recommend the appropriate technical path for each request, including whether to configure, automate, build, buy, integrate or decline a solution.
• Create internal AI solutions and take them from prototype through governed release and ongoing improvement using PAR-approved platforms and tools.
• Define solution requirements, architecture, dependencies, risks, delivery estimates and success measures.
• Make practical tradeoffs across user experience, quality, speed, cost, maintainability and risk.
• Build reusable solution patterns, components, Skills, agents, prompts and knowledge structures for use across teams.
• Own AI solutions after launch from the AI Enablement side, including quality, reliability, user feedback, adoption, cost and continuous improvement; partner with IT and Enterprise Systems as solutions transition into formal production and support processes.
• Establish appropriate evaluation, monitoring, issue management and human-review processes for each solution.
• Troubleshoot solution behavior and coordinate resolution across AI platforms, configurations, knowledge sources and enterprise dependencies.
• Maintain solution documentation, release notes, support guidance and ownership records.
• Retire, redesign or consolidate solutions that do not deliver sufficient value or cannot be supported responsibly.
• Partner with IT, Enterprise Systems and Security on identity, permissions, data access, environment, supportability and production-readiness requirements.
• Translate business use cases into technical designs that enterprise teams can review and support.
• Create solutions that can transition into PAR’s formal production processes as pathways and standards mature.
• Coordinate technical reviews, resolve blockers and ensure long-term ownership is clear before broader deployment.
• Identify when integrations are required and partner with appropriate technical teams or specialized builders when deeper integration work is needed.
• Review and triage incoming AI solution requests based on business value, feasibility, reuse potential, risk, effort and ongoing support cost.
• Clarify the underlying workflow before recommending a tool or technical approach.
• Maintain a prioritized delivery roadmap and communicate scope, decisions, status and dependencies to stakeholders and the VP of AI Enablement.
• Prevent one-off experimentation from becoming unsupported production tooling.
• Evaluate AI workloads across cost, quality, latency, usage and business value.
• Recommend model, platform or architecture changes that lower cost without weakening the required outcome.
• Validate new models and feature releases against PAR use cases before recommending broader adoption.
• Support leadership reporting with technical status, delivery forecasts, usage patterns and cost-optimization opportunities.
• Ensure AI solutions align with PAR standards for data handling, access, permissions, documentation and auditability.
• Participate in AI policy and standards development with IT, Security, Legal, Internal Audit and AI Enablement leadership.
• Define practical quality gates for prototypes, limited releases and broader deployment.
• Help business teams understand responsible ownership after an AI solution launches.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed