AI Lead Solutions Architect
Workana · Toronto, Ontario, Canada · On-site
Posted Oct 4, 2026
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About Workana
Workana is the largest remote work platform for talent in Latin America. Our division focuses on matching exceptional professionals with leading and innovative companies around the globe.
About the Client
Our client is a premier global financial institution committed to driving innovation and technical excellence across its core banking and digital services. They are looking for an experienced AI Lead Solutions Architect to drive strategic artificial intelligence and machine learning initiatives, architect scalable solutions, and mentor engineering teams.
This is a hybrid opportunity for professionals based in Toronto, Canada, working closely with an international team in an English-speaking environment.
Role Overview
As an AI Lead / Solutions Architect, you will lead R&D efforts and technical execution for complex AI/ML applications in financial services, including document intelligence, automated decisioning systems, and multi-agent workflows. You will design end-to-end architectures from model design to scalable production deployment while driving technical innovation using modern AI techniques such as retrieval-augmented generation (RAG) and transformer models.
In addition to technical ownership and architecture design, you will mentor junior engineers, guide team members in AI/ML concepts, and lead cross-functional project execution across ML engineers, backend developers, and business stakeholders to turn technical capabilities into tangible business outcomes.
Selection Process
The process usually consists of 3 stages and takes on average 4 weeks to be completed, depending on eventual additional technical rounds or take-home tests.
Initial interview with Workana's recruiting team;
Cultural fit interview with the client;
Final interview with C-level.
As Workana has multiple clients, if you pass the first round with Workana's recruiting team, you may also be considered for other relevant opportunities if the initial opportunity does not move forward.
Responsibilities
Architect and deploy end-to-end AI/ML solutions from model design to scalable production environments using modern frameworks.
Lead R&D initiatives in AI/ML applications including document intelligence, text extraction, and automated decisioning systems.
Drive technical innovation through experimentation with RAG, multi-agent systems, and transformer architectures.
Establish, maintain, and optimize deployment and monitoring pipelines for production AI models.
Coordinate cross-functional technical delivery across ML engineers, backend developers, data teams, and business stakeholders.
Develop technical project roadmaps, solution designs, load planning, and system optimization strategies.
Provide technical leadership and mentorship to junior engineers through code reviews, best practices, and algorithm selection.
Partner with business stakeholders to translate complex AI concepts into measurable business value and ROI.
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