AI Agent Engineer – Commercial AI Transformation
$120,000–$150,000 year
On-siteVancouver, British Columbia, Canada
Job Summary
Map business processes and design, build, and deploy AI agents that automate workflows across sales, customer success, and internal operations. Refine agents through iteration to handle edge cases and improve reliability, then apply rigorous engineering practices once moving toward production. Build and maintain data pipelines pulling from source systems like Microsoft Graph and Snowflake into a data warehouse, applying filtering and sensitivity handling before indexing. Work within an iPaaS platform to connect systems, enforce access control boundaries, and integrate with enterprise search tools while respecting existing governance. Drive adoption of version control, testing, and release discipline across the team, ensuring agents scale from prototype to production-grade deployment.
Required Qualifications
- Fully on-site position for the first six months
- Attendance in the office five days per week
- Bachelor's degree in Computer Science, AI/ML, or a related field
- 4+ years building software
- Demonstrated experience automating business processes at meaningful scale
- Strong software development lifecycle (SDLC) fundamentals: version control (Git), code review practices, testing, and release/deployment discipline
- Hands-on experience building integrations or data pipelines using an iPaaS/automation platform (e.g., Workato, Boomi, Mulesoft, or similar)
- Experience working with a cloud data warehouse (e.g., Snowflake) for data ingestion, transformation, or processing
- Recent hands-on experience designing, building, and deploying LLM-based agents or agentic workflows into production
- Working understanding of enterprise identity and access concepts (SSO, OAuth, group-based permissions) and how they constrain what a pipeline or agent can access
- Demonstrated judgment about when to move fast and informal (PoC stage) versus when to apply full engineering rigor (production stage)
- Genuine interest in and some exposure to how a commercial org (sales, CS, or ops) functions
Desired Qualifications
- Experience with enterprise search or knowledge platforms (e.g., Glean) and how they scope and surface indexed content
- Familiarity with Microsoft 365 ecosystem tooling relevant to data governance (e.g., Purview, Defender, Graph API)
- Experience working with SIEM or logging platforms (e.g., Panther, Splunk) from an integration or engineering standpoint
- Experience in a presales, customer success, or commercial operations environment
- Familiarity with Salesforce or similar commercial data systems
- Experience mentoring or upskilling less traditionally-trained engineers on SDLC best practices
- Test-Driven Development experience
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