AI Lead Solutions Architect
Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 4, 2026. Workana scores A on the Alion truth index.
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.
Requirements
- 10+ years of professional software development or relevant research experience with a strong background in Python.
- 3+ years of hands-on experience building and deploying AI/ML solutions in production environments.
- Expert proficiency in Python and solid familiarity with web technologies and frameworks (FastAPI, Django, or Flask).
- Hands-on experience with modern AI/ML frameworks including PyTorch, TensorFlow, Keras, HuggingFace, and LangChain.
- Proven technical expertise in NLP, modern transformer architectures, RAG, and multi-agent systems.
- Solid experience with relational databases (PostgreSQL), data processing pipelines, and ETL processes.
- Proven track record of architecting full-stack systems, leading complex AI projects, and mentoring engineering talent.
Bonus Points
- Experience in financial services or highly regulated industries.
- Hands-on experience with advanced document processing, PDF parsing, and text extraction pipelines.
- Familiarity with prompt engineering and large language model (LLM) optimization strategies.
- Publications or research contributions in AI/ML conferences or journals.
- Available to work in the office 2 to 3 days per week.
Benefits
- Compensation in CAD.
- Career growth with international clients and dynamic projects.
- This is a long-term independent contractor agreement with no additional benefits.