1 день назад
AI Lead Solutions Architect
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Lead Solutions Architect (AI/ML): Architecting and deploying end-to-end AI/ML solutions for financial services, including document intelligence, automated decisioning systems, and multi-agent workflows with an accent on scalable production architecture, RAG, and transformer models. Focus on leading R&D, optimizing deployment and monitoring pipelines, coordinating cross-functional delivery, and mentoring engineers.
Location: Toronto, Ontario, Canada; hybrid, with availability to work in the office 2 to 3 days per week
Company
is a remote work platform connecting professionals in Latin America with international companies; this opportunity supports a global financial institution.
What you will do
- Architect and deploy end-to-end AI/ML solutions from model design through scalable production environments.
- Lead R&D initiatives involving document intelligence, text extraction, automated decisioning, and multi-agent systems.
- Drive experimentation with retrieval-augmented generation, transformer architectures, and modern AI frameworks.
- Establish and optimize deployment, monitoring, load-planning, and system-optimization strategies for production models.
- Coordinate delivery across ML engineers, backend developers, data teams, and business stakeholders.
- Mentor junior engineers through code reviews, best practices, algorithm selection, and technical guidance.
Requirements
- 10+ years of professional software development or relevant research experience.
- Strong Python background and familiarity with FastAPI, Django, or Flask.
- 3+ years of hands-on experience building and deploying AI/ML solutions in production.
- Experience with PyTorch, TensorFlow, Keras, HuggingFace, LangChain, NLP, transformer architectures, RAG, and multi-agent systems.
- Experience with PostgreSQL, data-processing pipelines, ETL processes, and full-stack system architecture.
- Proven experience leading complex AI projects and mentoring engineering talent.
Nice to have
- Experience in financial services or highly regulated industries.
- Experience with document processing, PDF parsing, and text-extraction pipelines.
- Familiarity with prompt engineering and LLM optimization strategies.
- AI/ML publications or research contributions.
Culture & Benefits
- Long-term independent contractor agreement.
- International clients and dynamic projects.
- Compensation in USD.
- No additional benefits are included.
Hiring process
- Initial interview with 's recruiting team.
- Cultural-fit interview with the client.
- Final interview with a C-level executive; additional technical rounds or take-home tests may be included.
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