Context Engineer (AI)

TL;DR

Context Engineer (AI): Integrating large language models and agentic workflows into a wealth management platform with an accent on production reliability and RAG pipelines. Focus on designing context management strategies, building output validation layers, and developing evaluation frameworks for AI performance.

Location: Remote within Canada (Montreal, Ottawa, Toronto)

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

Company

hirify.global is a software platform for wealth management enterprises helping 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 with a focus on production-readiness.
• Architect and maintain RAG pipelines connecting language models to internal knowledge bases and live data sources.
• Manage context window strategies, optimizing information format and compression for accuracy, cost, and latency.
• Design and implement agentic workflows to handle multi-step, autonomous tasks.
• Build guardrail and output validation layers to ensure AI features operate within compliant boundaries.
• Develop evaluation frameworks to measure context effectiveness and agent reliability in production.

Requirements

• 5+ years of professional software engineering experience.
• 1–2 years of experience working with LLMs in a production context.
• Strong experience with Python or Node and building API-integrated backend services.
• Working knowledge of RAG architecture, vector databases (e.g., Pinecone, pgVector, AWS OpenSearch), and semantic search.
• Familiarity with context management techniques such as summarization, chunking, and memory strategies.
• Must be based in or eligible to work from Canada (specifically Ontario or Quebec).

Nice to have

• Experience with the Model Context Protocol (MCP) or similar tool-integration standards.
• Familiarity with LLMOps practices: tracing, observability (e.g., LangSmith, Datadog), and model versioning.
• Exposure to multi-agent architectures and orchestration patterns.
• Knowledge of AI output validation and governance in regulated financial industries.
• Familiarity with AWS cloud infrastructure and containerized deployments (Docker, Kubernetes).

Culture & Benefits

• Compensation aligned with competitive market data based on experience and location.
• Total rewards package including variable pay, equity, and comprehensive benefits.
• Flexible time off and dedicated opportunities for growth and development.
• Collaborative work environment built on trust, respect, and innovation.