Lead AI Solutions Architect — Remote

resourcepro

United States

Remote

USD 123,000 - 205,000

Full time

14 days+

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Benefits offered by this job

100% paid employee health insurance on

Eligible for medical, dental, vision—1

Internet stipend for remote roles

401k with employer match

HSA/FSA available

Long Term/Short Term disability

Generous PTO + holidays

Development and growth opportunities

Comprehensive wellness program

Job summary

ReSource Pro is seeking a Principal AISolutions Architect to design, validate, and define AI-driven solutions for client operations. This autonomous role sits at the intersection of client engagement, AI product design, and business strategy, translating insurance workflows into scalable AI-enabled solutions.

The ideal candidate has 8–12+ years in architecture, hands-on AI/LLM experience, and strong stakeholder management.

Qualifications

Bachelor's degree in Computer Science, Engineering, Business, or related field (Master’s preferred).
8–12+ years in solutions architecture, product strategy, or technical consulting.
Hands-on AI/ML technologies, LLMs, and automation experience.
Proven client-facing solution design and end-to-end architecture.
Ability to prototype and validate complex technical solutions independently.
Strong stakeholder management and cross-functional influence.
Deep understanding of insurance industry workflows or related environment.
High autonomy and comfort navigating ambiguity in an innovation role.

Responsibilities

Lead structured discovery sessions with clients to assess workflows and technology environments.
Architect end-to-end solutions across people, process, and technology components.
Develop prototypes independently using AI/ML tools, LLM APIs, and low-code platforms.
Design and execute proof-of-concept models to demonstrate business value and feasibility.
Translate validated use cases into scalable APM modules and detailed production specifications.
Serve as a primary intake point for AI-related opportunities across the organization.
Partner with AI Factory engineering teams to ensure clarity of requirements during handoffs.
Define success criteria, performance expectations, and technical constraints for AI solutions.
Collaborate with Sales and leadership to evaluate feasibility and fit of new opportunities.
Monitor alignment between designed solutions and delivered outcomes for continuous improvement.