Senior AI Automation Engineer
New
J
JobgetherAI automation
Workplace type: Remote; based in CanadaFull-TimeSenior
Salary110,000 - 160,000 CAD per year
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Job Details
- Required Skills
- Data AnalysisQA AutomationRESTful APIsScriptingPrompt Engineering
Requirements
- Demonstrated experience designing, building, and deploying automations, internal tools, or AI-powered workflows that deliver measurable business results.
- Strong practical knowledge of LLMs, AI agents, retrieval-augmented generation (RAG), and prompt engineering.
- Experience integrating APIs, scripts, existing business systems, and no-code or low-code automation platforms.
- Ability to understand user needs, clarify ambiguous requirements, and prioritize solutions by potential impact.
- Ability to move quickly from concept to working prototype, validate assumptions, and refine solutions without overengineering.
- Sound technical judgment about when solutions need production-grade reliability, monitoring, and scalability.
- Strong written and verbal communication skills, including explaining technical concepts and trade-offs to non-technical audiences.
- Ability to work with data by extracting, cleaning, interpreting, and using it to support business decisions.
- Strong analytical, organizational, and problem-solving skills.
- Ability to collaborate across teams, adapt to changing priorities, take ownership, and communicate progress and challenges transparently.
- Experience mentoring, training, or supporting non-technical colleagues building tools and automations is an asset.
- Experience in internal tools, Revenue Operations (RevOps), Business Operations (BizOps), or applied AI is an advantage.
Responsibilities
- Collaborate with business stakeholders to understand workflows and prioritize automation opportunities.
- Translate business challenges into technical requirements and build AI-powered automations, internal tools, and integrations.
- Develop and deploy prototypes, validate their impact with stakeholders, and iterate based on feedback and outcomes.
- Connect LLMs, AI agents, RAG, and prompt engineering techniques with existing business systems.
- Prepare successful prototypes for production with monitoring, observability, error handling, documentation, and reusable components.
- Coach non-technical colleagues through guidance, reviews, troubleshooting, workshops, and office hours.
- Create shared templates, prompt libraries, integration patterns, and automation components.
- Partner with Engineering and IT on platform decisions, technical standards, and infrastructure.
- Track business impact using measures such as time saved, reduced error rates, and shorter processing cycles.
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