Senior Software Engineer — AI/ML Infra & Cloud

Genesys; Toronto; On-site; CAD 173,000 - 227,000; Full time

Benefits offered by this job

Paid volunteer time

August Free Fridays

Well-being resources

Regionally tailored programs for员工 and

Job summary

Genesys is seeking a Senior Software Engineer to design and build scalable cloud, big data, and ML infrastructure powering AI-driven workforce management. The role offers opportunities to collaborate with data scientists and product teams, shape architecture, and deliver production-grade systems.

You will influence technical direction, lead projects end-to-end, and mentor engineers while improving reliability, observability, and cost efficiency across data platforms in a fast-paced, enterprise

Qualifications

• Proven experience designing production-grade data pipelines.
• Strong AWS/cloud-native architecture background.
• Experience with distributed data processing and ML platforms.
• Ability to lead projects from design through production.
• Excellent collaboration with data scientists and engineers.

Responsibilities

• Translate requirements into scalable AI/ML infrastructure designs.
• Lead end-to-end cloud, Big Data, and ML infrastructure projects.
• Design and develop distributed data pipelines and workflow orchestration services.
• Improve platform reliability, observability, security, and cost efficiency.
• Provide technical guidance and mentoring to junior engineers.

Skills

Five+ years experience

Python/Java/Scala

Distributed systems

AWS cloud

Mentoring

CI/CD

Big Data (Spark)

Education

Bachelor’s degree in CS/Engineering or related field

Tools

Spark

EMR

S3

Metaflow

AWS Batch

Step Functions

Fargate

Airflow

Kubeflow

Terraform

CloudFormation

OpenTelemetry

New Relic

Job description

Genesys is seeking a Senior Software Engineer to design and build scalable cloud, big data, and ML infrastructure powering AI-driven workforce management. The role offers opportunities to collaborate with data scientists and product teams, shape architecture, and deliver production-grade systems.

You will influence technical direction, lead projects end-to-end, and mentor engineers while improving reliability, observability, and cost efficiency across data platforms in a fast-paced, enterprise