AI Platform Engineer
- Salary
- CA$90K–CA$100K
- Hiring from
- Canada
- Work type
- Hybrid
- Posted
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About Us
Infoya is a global IT solutions provider specializing in transforming complex challenges into streamlined, AI-powered outcomes. Through proprietary technology accelerators and full-scale enterprise services, Infoya automates workflows, enhances operational efficiency, and drives digital transformation across industries. With a presence in Canada, the US, India, and Costa Rica, we blend technical depth with creative problem-solving to deliver measurable impact.
Job Description
About the Job: We’re looking for a hands-on AI
Platform Engineer to build and operate production-ready LLM agent systems and
anomaly detection tools. You’ll 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.
Requirements
Required Qualifications:
- Bachelor’s 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.
Benefits
Salary Range: CAD$ 90,000 - 100,000
The final compensation offered will depend on local market
conditions and geographic location, as well as job-related factors such as the
candidate’s knowledge, skills, qualifications, relevant experience, and
education/training. Compensation may also include additional components such as
benefits, and/or other incentives, where applicable. In 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.
