AI Solution Architect / FDE (AWS and Azure) -

Role overview

Architecture and engineering

• Architect end-to-end AI/ML solutions and scalable applications, APIs, data pipelines, and workflows.
• Evaluate emerging technologies and make decisions involving Generative AI, RAG, LLMs, multi-agent systems, NLP, and transformer models.
• Lead production AI/ML development, model evaluation, RAG and LLM application design, and document processing use cases.
• Establish standards for secure, reliable, scalable, and maintainable solutions while balancing business needs, performance, security, and cost.
• Build APIs and services integrating AI into enterprise applications; establish model evaluation, monitoring, and continuous improvement.

Technical leadership and delivery

• Lead AI initiatives from discovery and prototyping through production; own architecture, technical design, implementation strategy, and delivery planning.
• Coordinate AI/ML, software, data science, infrastructure, and business teams; turn business needs into technical roadmaps.
• Identify risks, dependencies, and opportunities and support transition from proof of concept to scalable production.

AI platform, DevOps, and mentorship

• Design AI/ML deployment pipelines and practices for model deployment, monitoring, versioning, testing, and lifecycle management.
• Integrate AI solutions with enterprise systems, APIs, databases, and data platforms; promote automation and repeatable engineering.
• Mentor technical staff, guide model and architecture choices, review code and designs, and encourage documentation and knowledge sharing.

Required qualifications

• 10+ years of professional software engineering, technology, or relevant research experience and 3+ years of production AI/ML engineering experience.
• Expert Python skills and strong experience designing and implementing end-to-end AI/ML solutions.
• Experience with modern frameworks such as PyTorch, TensorFlow/Keras, Hugging Face Transformers, or LangChain or comparable LLM frameworks.
• Strong knowledge of Generative AI, LLMs, RAG, NLP, and transformer architectures.
• Production API and service development using technologies such as FastAPI, Flask, or Django; REST API and integration knowledge.
• SQL and relational database experience, including PostgreSQL, and data processing and ETL pipeline development.
• Experience leading complex technical initiatives across teams and communicating technical ideas to technical and business audiences.

Preferred qualifications

• Multi-agent systems, prompt engineering, LLM optimization, AI evaluation, document intelligence, PDF parsing, OCR, or text extraction experience.
• Financial services or other regulated-industry delivery; enterprise AI governance, security, responsible AI, or model risk experience.
• Cloud AI/ML platforms, MLOps, full-stack development including JavaScript, enterprise integrations, or published AI/ML contributions.

Compensation

• The posting lists a CAD 163,697–CAD 252,175 target compensation range for the remote role; compensation varies by location, experience, skills, and qualifications.

Workplace

• The posting describes the position as remote and notes that arrangements may change with client requirements; office or client-site attendance may be required for some meetings or events.

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