Context Engineer (AI)

TL;DR

Context Engineer (AI/LLM): Designing and implementing LLM-powered features and agentic workflows for a wealth management platform with an accent on RAG pipelines and context window strategy. Focus on building production-ready AI infrastructure, implementing guardrail layers, and developing evaluation frameworks to ensure reliability and accuracy.

Location: Remote, but must be based in Montreal, Ottawa, or Toronto, Canada

Salary: $120,000 - $140,000 CAD

Company

hirify.global is a software platform for wealth management enterprises that helps financial advisors explain complex investment strategies to their clients.

What you will do

• Design and implement LLM-powered features using APIs from Anthropic, OpenAI, and Cohere.
• Architect and maintain RAG pipelines connecting models to internal knowledge bases and live data.
• Optimize context window strategies for accuracy, cost, and latency.
• Build agentic workflows for multi-step autonomous tasks and develop reusable agent primitives.
• Create guardrail and output validation layers to ensure compliant model behavior.
• Develop evaluation frameworks and monitor deployed systems for failure patterns.

Requirements

• Must be based in or eligible to work from Ontario, Quebec (specifically Montreal, Ottawa, or Toronto).
• 5+ years of professional software engineering experience.
• 1–2 years of experience working with LLMs in a production context.
• Proficiency in Python or Node for building API-integrated backend services.
• Working knowledge of RAG architecture and vector databases (e.g., Pinecone, pgVector, AWS OpenSearch).
• Experience with REST APIs and third-party service integrations.

Nice to have

• Experience with Model Context Protocol (MCP).
• Familiarity with LLMOps (LangSmith, Datadog) and model versioning.
• Exposure to multi-agent architectures and orchestration patterns.
• Knowledge of AI governance in regulated financial services.
• Experience with AWS, Docker, and Kubernetes.

Culture & Benefits

• Compensation aligned with competitive market data based on experience and location.
• Total rewards include variable pay and equity.
• Comprehensive benefits package.
• Flexible time off.
• Dedicated opportunities for professional growth and development.