Role: AI Architect Location: Ontario, Canada (Remote only) Type: 6+ month contract

Job Description - Day to Day job Duties: (what this person will do on a daily/weekly basis) As an AI Architect, you will design and build agentic AI systems for multiple Domains such as Healthcare/ Finance/ Retail etc. You will combine GenAI, ML, and systems engineering to create AI agents that interact with machines, data streams, and enterprise systems.

Key Responsibilities:

• Design and implement agent-based AI workflows for different domains such as :
• healthcare use cases (clinical assistants, triage agents, care pathway optimization, RCM automation)
• Design agentic AI architectures for manufacturing workflows
• Build multi-agent financial AI systems (analysis agents, compliance agents, advisory agents)
• Implement RAG over financial documents, policies, contracts, and filings
• Build LLM-powered systems (RAG, tool-calling agents, multi-agent orchestration)
• Develop classical ML models (risk scoring, prediction, clustering, anomaly detection)
• Implement HIPAA aware AI architectures with auditability and traceability
• Implement GenAI systems using RAG over CRM, customer data, and content
• Build full-stack applications (Python APIs, AI services, UI dashboards)
• Integrate with EHRs, data lakes, and healthcare systems (FHIR/HL7 exposure preferred)
• Integrate LLMs with sensor data, MES, ERP, and IoT platforms
• Collaborate with SMEs to translate medical workflows into agent logic
• Deploy, monitor, and optimize AI systems in Azure

Basic Qualifications: (what are the skills required to this job with minimum years of experience on each)

• Strong experience in Python-based AI systems - 8+ Years
• Hands-on experience with GenAI (LLMs, RAG, embeddings, prompt engineering) - 8+ Years
• Experience with traditional ML (classification, regression, NLP, time-series)
• Full-stack experience (API design + UI integration) - 5+ Years
• Azure cloud experience (Azure ML, Azure OpenAI, Functions, AKS) - 5+ Years
• Experience working in regulated or compliance-heavy domains
• Comfortable working with subject-matter experts
• Strong learning mindset and adaptability
• Experience building production AI systems, not just prototypes
• Ability to explain AI decisions to non-technical stakeholders
• Interest in agentic AI and next-generation AI architectures

Degree: Bachelors in Computer Science or equivalent work experience Nice to Have; (But not a must)

• Multiple Domain exposure
• AWS, GCP, or NVIDIA AI stack experience
• Knowledge of model governance and explain ability
• Experience with document intelligence pipelines