AI Solution Architect
Application Deadline
Address
Job Family Group
Who We Are
What You’ll Do
agentic AI journeys, machine learning, and intelligent workflow automation
Qualifications
- Strong experience designing
end-to-end enterprise AI solution architectures
, including integration across business applications, data platforms, APIs, AI/ML services, and cloud technologies
- Demonstrated understanding of
agentic AI architectures
, including multi-agent orchestration, agent/tool interaction, workflow and state management, event-driven patterns, human-in-the-loop design, knowledge retrieval, and AI guardrails
- Experience translating complex business processes and user journeys into scalable technical and solution architectures
- Strong understanding of
machine learning and Generative AI concepts
, including predictive modeling, LLMs, retrieval-augmented generation, embeddings, model evaluation, and the AI/ML lifecycle
- Demonstrated proficiency with Python and SQL, with the ability to work effectively with AI, data science, data engineering, and software engineering teams
- Experience across the full AI solution lifecycle, from business challenge and architecture through development, integration, deployment, monitoring, and ongoing evolution
- Knowledge of enterprise integration patterns including APIs, event-driven architectures, messaging, workflow orchestration, and integration with systems of record
- Experience designing AI solutions with appropriate consideration for
security, privacy, responsible AI, model risk, resiliency, observability, and enterprise controls
- Strong business stakeholder engagement skills, with the ability to communicate complex architectural concepts to both technical and non-technical audiences
- Ability to lead solution design across multidisciplinary teams and provide technical direction and mentorship to architects, engineers, data scientists, and AI practitioners
- Experience in financial services, with
Commercial Banking domain knowledge
considered a strong asset, including familiarity with areas such as lending, underwriting, credit, onboarding, relationship management, treasury and payments
- Ability to balance business value, user experience, technical feasibility, risk, cost, scalability, and time-to-market when making architecture decisions
- 10+ years of relevant experience across financial services, AI/ML, solution architecture, data, or software engineering
- Advanced degree in a relevant field such as computer science, engineering, data science, artificial intelligence, statistics, mathematics, or a related discipline
- Knowledge of cloud platforms such as
AWS or Azure
Salary
About Us
Not included in the source posting: benefits.
Skills
Who can apply
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