The RoleThe
AI Solutions Architect is responsible for designing, implementing, and scaling AI-enabled solutions across TheGuarantors' customer-facing and internal operations. This role supports the AI function by translating high-impact business opportunities into secure, reliable, measurable, and production-ready systems.
The ideal candidate will bring strong technical architecture, integration, automation, and AI implementation experience and will be expected to work closely with Data Engineering, Software Engineering, Data Science, Business Analytics, Claims, Underwriting, Ops, Finance, vendors, and stakeholders to evaluate solutions, design scalable workflows, and help bring AI initiatives from pilot to production.
LocationThis is a hybrid role based in NYC
What You'll Do- Own solution architecture for AI-enabled workflows across customer-facing and internal operational processes.
- Execute day-to-day responsibilities related to AI solution design, integration planning, vendor implementation, testing, and launch readiness with accuracy, timeliness, and consistency.
- Analyze, review, and maintain technical requirements, workflow documentation, integration designs, data needs, and implementation plans to support business needs.
- Partner with Data Engineering, Software Engineering, Data Science, Business Analytics, Claims, Underwriting, Ops, Finance, vendors, and stakeholders to support AI initiatives and ensure alignment.
- Communicate updates, risks, blockers, technical tradeoffs, and recommendations clearly and proactively.
- Identify opportunities to improve process efficiency, system reliability, automation quality, customer experience, compliance, and operational outcomes.
- Use data, technical judgment, and business context to inform architecture decisions and recommendations.
- Manage assigned work independently and follow through on commitments, deadlines, and deliverables.
- Ensure AI solutions are designed and implemented in accordance with applicable policies, procedures, standards, data governance expectations, and regulatory requirements.
- Perform other role-related responsibilities as assigned and aligned with business needs.
What You Bring- 6+ years of experience in solutions architecture, data engineering, software engineering, platform engineering, technical product, or a similar technical role.
- Experience with production systems, APIs, internal tools, workflow automation, data products, vendor integrations, or AI-enabled applications.
- Strong understanding of system architecture, data quality, security, permissions, monitoring, auditability, and operational risk.
- Demonstrated ability to manage technical solution design, partner with cross-functional stakeholders, and deliver high-quality work in a dynamic business environment.
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience.
Preferred Qualifications- Experience working in a fast-paced, high-growth, technical, operational, or regulated environment.
- Experience using systems and tools such as Zendesk, HubSpot, Decagon, Sierra, Ada, Claude, OpenAI, Snowflake, dbt, Power BI, GitHub, or similar platforms.
- Additional education, certification, or training in AI, data engineering, software engineering, cloud architecture, security, or product technology.
- Prior experience in fintech, insurance, proptech, real estate operations, claims, underwriting, customer support automation, or workflow transformation.
Benefits- Opportunities to make an impact within a fast growing company
- Medical, dental, & vision insurance, beginning day one
- Health savings account with employer contribution
- Flexible spending accounts (healthcare, dependent care, commuter)
- 401(k)
- Generous PTO and paid holidays
- In-office lunch Perk
- Flexible working hours
- Paid parental leave
- Company sponsored short and long term disability
Base SalaryThe base salary range is between $200,000 - $230,000 annually.
Base salary does not include other forms of compensation or benefits. Final offer amounts are determined by multiple factors, including prior experience, expertise, location and current market data and may vary from the range above.
