7 дней назад
Applied AI Engineer (AI)
140 000 - 160 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Applied AI Engineer (AI/LLM): Building production-grade agentic workflows and AI infrastructure for an employee communications SaaS platform with an accent on orchestration, evaluation, reliability, and data residency. Focus on designing multi-step agents, creating regression harnesses, deploying AI workloads on EKS, and controlling hallucination, latency, cost, and privacy risks.
Location: Toronto, Canada; hybrid work with office attendance three times per week or as needed at the downtown Toronto office
Salary: $140,000–$160,000 per year
Company
provides an employee communications SaaS platform with email creation, delivery, engagement measurement, and analytics integrated with Outlook and Gmail.
What you will do
- Design, prototype, and ship production-grade agentic workflows using dynamic routing, tool-using agents, and feedback loops.
- Build evaluation harnesses, datasets, automated grading, and offline regression suites for AI features.
- Develop AI infrastructure and deployment paths on AWS EKS with SRE and platform engineers.
- Instrument token spend, latency, failure rates, and model quality while designing graceful failure handling.
- Manage prompts and model configurations as versioned, reviewable, and rollback-ready code.
- Ensure regional data residency, model-invocation logging, prompt safety, and protection against injection and PII exposure.
Requirements
- Bachelor’s degree or equivalent practical experience in computer science, statistics, mathematics, engineering, or a related field.
- 3+ years of professional software engineering experience, including hands-on AI/ML or LLM-powered feature development.
- Fullstack experience with Ruby on Rails or another backend framework and Vue.js, React, or another frontend framework.
- Hands-on infrastructure-as-code experience, preferably with Terraform, plus working knowledge of AWS, IAM, networking, secrets management, and containerized workloads.
- Experience taking LLM features from prototype to production, including structured outputs, function calling, evaluation, reliability, latency, cost, and safety considerations.
- Familiarity with RAG architectures, vector stores, agile development, collaborative work, and clear written and oral communication.
Nice to have
- Experience building agentic systems, evaluation harnesses, or operating AI in production.
- Experience with Amazon Bedrock, model routing, provider abstraction, or AI coding agents.
- Experience in the email ecosystem or another high-scale communications platform.
Culture & Benefits
- Hybrid work from the downtown Toronto office with collaboration-focused in-person attendance.
- Employer-paid benefits and a Health Spending Account from the first day.
- RRSP group savings plan and stock option plan.
- Generous vacation, health days, a personal day, volunteering days, and a birthday day off.
- Personal development budget and access to a fully stocked office.
Hiring process
- Applications and interviews are reviewed by the Talent Acquisition team.
- AI is used to take interview notes and support applicant-tracking workflows.
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