Platform - SRE Engineer

Anticipated Contract End Date/Length: November 30, 2026.

Work Set Up: Hybrid (3 days per week in office)

Clearance required: BPSS

Our client in the Information Technology and Services industry is looking for a Platform / SRE Engineer to own deployment, observability, reliability, cost control, and production operations for an AI helpdesk platform. This role will support the design, deployment, and operational management of AI services and production environments while ensuring scalability, uptime, performance optimization, and operational resilience across cloud-based infrastructure.

The ideal candidate will bring strong expertise in DevOps and Site Reliability Engineering practices, along with experience managing cloud-native platforms, CI/CD pipelines, observability tooling, and AI/ML production workloads within complex enterprise environments.

What you will do

• Build and manage CI/CD pipelines, infrastructure, and runtime environments for AI services.
• Deploy and operate model-serving, orchestration, and application workloads.
• Implement monitoring, tracing, alerting, logging, and operational dashboards.
• Manage scaling activities, release processes, rollback mechanisms, and production support operations.
• Optimize inference cost, latency, uptime, and overall system reliability.
• Create runbooks, operational standards, and incident response processes.
• Support infrastructure automation and platform engineering initiatives.
• Maintain observability and monitoring solutions across production environments.
• Support release automation, secrets management, and production operational processes.
• Collaborate with engineering teams to support AI platform reliability and operational readiness.
• Troubleshoot production issues and support system diagnostics and remediation activities.
• Ensure platform stability, scalability, and performance across cloud-native environments.
• Strong experience in DevOps and Site Reliability Engineering environments.
• Experience with Docker, Kubernetes, cloud platforms, and Infrastructure as Code practices.
• Strong experience with monitoring, observability, and operational tooling.
• Familiarity with CI/CD pipelines, release automation, secrets management, and production support processes.
• Understanding of LLM deployment patterns and API-based model integrations.
• Experience working with cloud platforms, particularly AWS.
• Experience using Jira, Confluence, and ServiceNow.
• Experience supporting AI/ML workloads in production environments is preferred.
• Experience with GPU workloads, autoscaling, and cost optimization is preferred.
• Strong troubleshooting, operational support, and incident response capabilities.
• Strong communication and collaboration skills within cross-functional engineering teams.

All your information will be kept confidential according to EEO guidelines.

Candidates must be legally authorized to live and work in the country where the position is based, without requiring employer sponsorship.

HelloKindred is committed to fair, transparent, and inclusive hiring practices. We assess candidates based on skills, experience, and role-related requirements.

We appreciate your interest in this opportunity. While we review every application carefully, only candidates selected for an interview will be contacted.

HelloKindred is an equal opportunity employer. We welcome applicants of all backgrounds and do not discriminate on the basis of race, colour, religion, sex, gender identity or expression, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic under applicable law.