Emerging Technology Architect

As passionate about our people as we are about our mission. Why Join Q2? Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our mission is simple: build strong and diverse communities through innovative financial technology—and we do that by empowering our people to help create success for our customers.

Being as passionate about our people as we are about our mission. We celebrate our employees in many ways through our year-round Q2 Change Makers awards program and global moments of recognition and connection. We invest in the growth and development of our team members through ongoing learning opportunities, internal mobility, and meaningful leadership relationships. We also know that nothing builds trust and collaboration like having fun and giving back together.

From company-wide volunteer days to events like our Q2 Homecoming Week—featuring learning, community service, and culture-building experiences—we create opportunities to connect, grow, and make an impact.

The Emerging Technology Architect designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end-to-end AI solution patterns involving large language models, APIs, retrieval-augmented generation, vector search, intelligent agents, orchestration workflows, Snowflake, cloud platforms such as AWS and Azure, and enterprise data integration. The role partners across data, engineering, business applications, operations, identity and access management, and governance teams to create reusable frameworks that accelerate delivery while supporting security, access controls, compliance, and audit needs.

This position may require minimal travel for collaboration, planning, or stakeholder engagement.

Design enterprise AI solution patterns that align business needs with scalable, secure, and maintainable implementation approaches. Collaborate with cross-functional teams to translate complex business challenges into structured architecture recommendations. Identify, analyze, and resolve gaps related to scalability, data readiness, interoperability, and operational adoption of AI systems. Define reusable frameworks and standards that improve delivery consistency and accelerate adoption across teams and use cases.

Evaluate solution options, assess trade-offs, and provide recommendations that balance performance, cost, risk, and business value. Guide teams through architecture decisions that support responsible AI adoption and long‑term maintainability. Influence organizational direction by promoting best practices, shared patterns, and practical governance approaches across engineering and business teams. Stay current on emerging AI and enterprise technology practices and assess their applicability to organizational priorities.

Bring Your Passion, Do What You Love.

Typically requires a Bachelor’s degree in (relevant degree) and a minimum of 12 years of related experience; or an advanced degree with 8+ years of experience; or equivalent related work experience. Strong understanding of enterprise architecture principles, system design, integration patterns, and scalable delivery models. Demonstrated experience with AI and machine learning technologies including large language models, retrieval-augmented generation, vector databases, intelligent agents, and cloud-based AI platforms (AWS, Azure, or equivalent).

Experience partnering with business and technical stakeholders to define practical solutions for complex organizational needs. Ability to evaluate ambiguous…