Senior AI Engineer (AI Automation)
New
J
JobgetherAI automation
Based in Canada, Approximately six hours of daily working-hour overlap with the team's core schedule, generally within the 8:00 a.m. to 5:00 p.m. Pacific Time window.Full-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonArtificial IntelligenceTypeScript
Requirements
- Strong software engineering experience with Python or TypeScript, including developing, maintaining, and deploying production-quality code.
- Advanced practical expertise in AI development and daily experience building agentic applications with current frontier models.
- Hands-on experience with Model Context Protocol (MCP), retrieval-augmented generation (RAG), model evaluation, and observability.
- Demonstrated ability to design, develop, and deploy production-ready AI agents, applications, and automated workflows.
- Provide a portfolio or concrete examples of personally built AI-powered solutions demonstrating technical depth and practical impact.
- Experience translating non-technical stakeholder requirements into effective technical solutions and identifying underlying problems.
- Sound judgment about when AI is appropriate, its limitations, and when alternative approaches are more effective.
- Experience building AI tools or internal applications adopted by non-technical teams.
- Daily experience using AI-assisted development tools such as Claude Code, Cursor, or equivalent.
- Strong understanding of software engineering best practices, including code quality, maintainability, testing, documentation, and production deployment.
- Experience building reusable components and scalable automation frameworks.
- Experience collaborating with engineering teams on technical standards, code reviews, shared infrastructure, and production reliability.
Responsibilities
- Design, build, and deploy AI-powered agents, applications, and automation workflows for Product, Product Marketing, and Design teams.
- Identify repetitive manual processes and turn them into intelligent automations.
- Work with product and business teams to understand challenges and translate needs into technical solutions.
- Develop agentic solutions using AI models, MCP, retrieval systems, evaluation frameworks, and observability tools.
- Build applications that give teams access to customer insights, business intelligence, and relevant data.
- Develop and maintain reusable AI components, shared agents, internal applications, and automation frameworks.
- Own the development lifecycle from opportunity identification and requirements through prototyping, deployment, monitoring, and improvement.
- Deliver prototypes quickly and make production improvements based on user feedback.
- Collaborate with engineering teams on technical standards, code reviews, shared infrastructure, and production quality.
- Evaluate where AI automation is valuable and when traditional software or human intervention is more appropriate.
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