AI Platform Engineer
Job Summary
About the Job: Were looking for a hands-on AI Platform Engineer to build and operate production-ready LLM agent systems and anomaly detection tools. Youll own solutions from design through deployment and monitoring apply practical AI governance and identify opportunities to improve how engineering and operations teams work.
Office Location: Toronto
Employment Type: Permanent
Role Type: New position current requirement
Work Arrangement: Hybrid (2 days in office)
Position Responsibilities:
- Design build and operate LLM agent systems using Google ADK or a comparable framework such as LangGraph CrewAI AutoGen or OpenAI Agents SDK.
- Own delivery end to end including architecture coding containerization CI/CD deployment to Kubernetes or cloud infrastructure and post-launch monitoring.
- Build agent tools as MCP servers and integrate with REST APIs.
- Address production concerns such as tool timeouts oversized responses retries and token costs.
- Develop or improve time-series forecasting and anomaly detection using production metrics such as Prometheus or Grafana data.
- Tune detection thresholds against real incidents and balance false positives against missed alerts.
- Use AI coding tools such as Claude Code Cursor or Copilot regularly as part of daily engineering work.
- Extend AI coding tools for team use through plugins skills slash commands hooks or MCP integrations.
- Review and verify AI-generated code before it ships.
- Apply safeguards to AI systems including code-enforced access controls PII and secrets handling audit logging cost limits and model output evaluation.
- Work with security and compliance teams through internal review processes.
- Identify opportunities by observing how engineering and operations teams work then prototype and deliver tools that people adopt.
Required Qualifications:
- Bachelors degree in Computer Science Engineering or related field (or equivalent experience).
- 4 years of experience shipping LLM agent system to production within a company.
- End-to-end experience with a production agent system including architecture implementation deployment through CI/CD to Kubernetes or cloud and monitoring after launch.
- Experience building agent tools as MCP servers and integrating with REST APIs.
- Understanding of production issues such as tool timeouts oversized responses retries and token cost management.
- Hands-on experience with time-series forecasting or anomaly detection on real production metrics.
- Experience tuning alert thresholds against real incidents and managing the trade-off between false positives and missed alerts.
- Regular use of AI coding tools as part of daily engineering work with a disciplined approach to reviewing and validating generated code.
- Practical experience making AI systems safe for enterprise use including access controls enforced in code PII and secrets handling audit logging cost limits and model evaluation.
- Comfort working within security and compliance review processes.
Preferred Qualifications:
- Experience extending AI coding tools for a team through custom plugins skills slash commands hooks or MCP integrations.
- Experience deploying and monitoring containerized services on Kubernetes or a cloud platform.
- Strong software engineering practices including testing observability CI/CD and production support.
- Ability to explain technical decisions and operational trade-offs to engineering operations and security stakeholders.
Salary Range: CAD$ 90000 - 100000
The final compensation offered will depend on local market conditions and geographic location as well as job-related factors such as the candidates knowledge skills qualifications relevant experience and education/training. Compensation may also include additional components such as benefits and/or other incentives where accordance with new employment standards requirements we retain copies of this job posting and applicant information for three (3) years after the posting is removed. We do not use AI technology; all applications are also reviewed by our recruitment team.