Staff AI Engineer

AItoolnavio

Canada

Remote

CAD 150,000 - 210,000

Full time

2 days ago
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Benefits offered by this job

Competitive salary package
High-autonomy role with direct AI road

Job summary

AItoolnavio is seeking a Staff AI Engineer based in Canada to lead the design, development, and delivery of high-impact AI initiatives. You will shape architectural decisions, build production-ready AI agents, and collaborate across Product, Design, QA, and Engineering to deliver measurable value.

The role emphasizes hands-on engineering with strategic influence, robust evaluation frameworks, and scalable shared AI infrastructure to support customer-facing AI capabilities.

Qualifications

  • Extensive experience leading major AI initiatives as a Staff-level engineer.
  • Proven track record deploying production-grade LLM apps and AI agents.
  • Strong backend/platform skills with Python and Django, PostgreSQL, Redis.

Responsibilities

  • Lead design, development, and delivery of major AI initiatives including AI-powered assistants and generative features.
  • Drive production AI systems from architecture to deployment with cross-functional teams.
  • Develop scalable AI quality frameworks, evaluations, and monitoring.

Skills

LLM applications
AI architecture
Python/Django
PostgreSQL
Redis
REST/GraphQL

Tools

Python
Django
PostgreSQL
Redis

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Engineer based in Canada.

As a Staff AI Engineer, you will play a key role in shaping and delivering high-impact AI initiatives, building production-ready solutions that directly improve customer experiences. You will provide technical leadership across engineering teams, influence major architectural decisions, and help define the future of the organization’s AI capabilities. Working within a collaborative, cross-functional environment, you will lead projects from initial design through production deployment. You will also strengthen the shared AI platform, establishing robust evaluation frameworks, quality standards, and scalable infrastructure. This is an opportunity to combine hands‑on engineering with strategic influence, building reliable AI systems that deliver measurable value to real users.

Accountabilities
  • Lead the technical design, development, and delivery of major AI initiatives, including AI-powered assistants, contextual data systems, and generative AI features.
  • Contribute directly to production AI systems from the outset, identifying technical opportunities and delivering improvements to existing architecture and workflows.
  • Drive early improvements in AI quality, reliability, and performance by addressing known failure points, strengthening evaluation coverage, and implementing measurable enhancements.
  • Take ownership of major AI projects from architecture and technical planning through cross-functional collaboration, deployment, and ongoing optimization.
  • Define and influence architectural decisions across engineering teams, with particular responsibility for AI architecture and shared platform infrastructure.
  • Establish scalable AI quality frameworks, including automated evaluations, regression testing, guardrails, agent tracing, human feedback mechanisms, and production monitoring.
  • Design and implement reliable AI agents and tool integrations, balancing deterministic code and LLM capabilities while addressing security, latency, reliability, and cost.
  • Drive broader engineering initiatives that improve development quality and velocity, such as AI evaluation standards, agentic software development practices, code review processes, and technical documentation.
  • Collaborate closely with Product, Design, QA, Operations, and engineering stakeholders to translate business needs into effective technical solutions.
  • Promote engineering excellence through technical mentorship, knowledge sharing, clear architectural standards, and a culture of continuous improvement.
Requirements:
  • Extensive experience in software engineering at Staff Engineer or equivalent level, with a proven ability to lead complex, ambiguous initiatives as a hands‑on individual contributor.
  • Demonstrated experience designing, building, and deploying production‑grade LLM applications, AI agents, or generative AI features used by real customers.
  • Strong technical leadership skills, including the ability to influence architectural decisions across teams, establish engineering standards, and drive initiatives from proposal through implementation.
  • Proven experience building and maintaining AI evaluation frameworks that combine automated testing, agent traces, human feedback, and production monitoring to measure quality and prevent regressions.
  • Strong understanding of AI agent architecture, tool design, and orchestration, including the ability to determine when deterministic logic is preferable to LLM‑based solutions.
  • Experience designing secure and reliable tool boundaries, human‑in‑the‑loop workflows, and systems that balance performance, latency, security, and operational costs.
  • Sound judgment in build‑versus‑buy decisions, model selection, and AI provider integrations.
  • Strong backend and platform engineering expertise, particularly with Python and Django, PostgreSQL, Redis, asynchronous workers, and REST or GraphQL APIs.
  • Ability to design scalable shared AI infrastructure with well‑defined interfaces, efficient caching strategies, and robust tenant isolation.
  • Excellent problem‑solving, communication, and collaboration skills, with the ability to work effectively across Product, Design, QA, and engineering teams.
  • A pragmatic, measurement‑driven approach to AI development, prioritizing evidence, evaluation, and reliability over simply changing models or rewriting prompts.
Benefits:
  • Competitive salary package.
  • Opportunity to build and ship production AI solutions used daily by real customers.
  • Broad technical scope across multiple AI products and the shared infrastructure supporting them.
  • Significant architectural influence and participation in major technical decision‑making processes.
  • Access to a valuable proprietary dataset drawn from approximately 1,200 aesthetic medical practices, supporting the development of differentiated AI capabilities.
  • High‑autonomy, high‑ownership Staff‑level individual contributor role with direct influence over the AI roadmap and engineering strategy.
  • Opportunity to contribute to meaningful technology that empowers independent business owners and supports the long‑term growth of small businesses.
  • Collaborative, inclusive, and ownership‑driven engineering culture that values speed, care, continuous learning, and simplicity.
  • A workplace that welcomes diverse backgrounds and perspectives, with accommodations available throughout the recruitment process.
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