AWS AI Solution Architect

Location: Canada (ON/QC)

Company

hirify.global delivers enterprise technology projects involving scalable AI solutions and collaboration with customer stakeholders.

What you will do

• Design and implement production-grade AI and agentic architectures based on business and technical requirements.
• Develop LLM-powered applications, autonomous agents, and multi-agent workflows using LangGraph, LangChain, and Amazon Bedrock.
• Design orchestration patterns covering tool use, routing, planning, memory, state management, human-in-the-loop workflows, and multi-agent collaboration.
• Build RAG architectures and integrate AI agents with enterprise systems, APIs, databases, SaaS platforms, and internal tools.
• Define scalable, secure, observable, and cost-efficient architectures; establish patterns for evaluation, testing, monitoring, IAM, encryption, PII handling, and prompt-injection protection.
• Support prototyping, implementation, troubleshooting, production readiness, performance optimization, documentation, and collaboration with engineering and business stakeholders.

Requirements

• 3+ years of experience in AI/ML, software architecture, solution architecture, or similar technical roles.
• Strong hands-on experience designing and implementing LLM-based applications and practical experience building AI agents or agentic workflows.
• Strong experience with Amazon Bedrock and AWS-based AI architectures.
• Experience with LangGraph and LangChain.
• Strong understanding of RAG, tool/function calling, agent orchestration, multi-agent systems, memory and state management, structured outputs, and human-in-the-loop workflows.
• Strong understanding of prompt engineering and context management, plus experience integrating LLM applications with external APIs, databases, and enterprise systems.
• Understanding of vector databases, embeddings, semantic search, retrieval techniques, cloud scalability, high availability, security, observability, and cost optimization.
• Experience designing APIs and backend services for AI applications and evaluating model quality, hallucination reduction, retrieval quality, latency, and cost.
• Ability to translate business requirements into practical AI architecture and implementation decisions and explain complex AI concepts to technical and non-technical stakeholders.

Nice to have

• Experience with AWS AgentCore and AWS AI platform services including Lambda, Step Functions, ECS, EKS, API Gateway, DynamoDB, and Aurora/RDS.
• Experience with Amazon OpenSearch Service, pgvector, Pinecone, or other vector databases; MCP-based integrations; and LLM observability or evaluation platforms.
• Experience designing AI solutions for sensitive or regulated data, applying MLOps/LLMOps practices, and managing production AI lifecycles.
• Experience with Python, modern AI application frameworks, distributed or event-driven architectures, Azure AI Foundry, or Google Vertex AI.

Culture & Benefits

• Long-term, full-time engagement with 16 days of paid time off and official public holidays.
• Health insurance and access to certifications, Udemy courses, Claude, and other work tools.
• Company events, team-building activities, gifts, and recognition.
• Friendly, open, and supportive culture with opportunities for career growth and without excessive bureaucracy.