Senior Gen AI Developer (AI Engineering)

TL;DR

Senior Gen AI Developer (AI Engineering): Building and improving AI-enabled product features from prototype to production with an accent on translating business problems into clear AI tasks. Focus on implementing end-to-end solutions, measuring quality using repeatable evaluation methods, and contributing to production readiness.

Location: Toronto, Canada

Salary: $86,900 - $107,000 CAD

Company

hirify.global's SaaS solutions empower revenue leaders globally to design smarter go-to-market strategies, maximize seller performance, and unlock untapped potential.

What you will do

• Build and maintain product features and supporting backend components, including services, integrations, and internal workflows.
• Write production-ready code and lightweight prototypes to validate ideas quickly.
• Create automated tests and proactively fix issues to keep releases stable.
• Support proof-of-concepts and experiments by setting up test cases, reviewing results, and improving areas where quality is weak.
• Document systems and workflows so others can run, maintain, and extend what you build.

Requirements

• 4+ years of overall software engineering experience, with at least 2+ years building and shipping production systems in product teams.
• 4+ years of hands-on technical experience writing production-quality code.
• Strong software engineering fundamentals, including system design and scalable architecture.
• Proficiency in Python and/or TypeScript (or similar), building APIs, services, and data pipelines.
• Experience with cloud platforms (AWS, GCP, or Azure), CI/CD pipelines, automated testing, and observability.
• An experimentation mindset — able to define metrics, build evaluation frameworks, and iterate quickly in ambiguous problem spaces.
• Strong interest in learning and applying GenAI technologies in practical, production environments.

Nice to have

• Hands-on experience with GenAI/LLMs, including prompt engineering, retrieval/RAG, embeddings, tool or function calling, fine-tuning, or evaluation pipelines.
• Familiarity with LLMOps practices such as experiment tracking, version control for prompts or models, and cost or latency optimization.
• Experience with tools such as LangChain/LangGraph, OpenAI, Anthropic, Azure OpenAI, and vector databases like Pinecone, FAISS, or Milvus.
• Contributions to open source, technical blogs, or conference talks.

Culture & Benefits

• Innovate with Purpose: Build impactful solutions for customers worldwide.
• Join Excellence: Work in a diverse, collaborative, and innovative team.
• Shape the Future: Lead in redefining revenue optimization.
• Grow Together: Unlock your potential in a supportive environment.