Senior Platform Engineer – AI/ML

Genesys; Toronto; On-site; CAD 125,000 - 164,000; Full time

Job summary

Genesys seeks a Senior Software Engineer to design and build scalable cloud, Big Data, and ML infrastructure powering AI-driven Workforce Management capabilities.

The ideal candidate combines strong software-engineering fundamentals with experience in AWS, distributed data processing, and production platform development, mentoring others and shaping the technical direction of data/ML platforms.

Qualifications

• Five or more years of professional software-engineering experience or equivalent with an advanced degree.
• Advanced programming experience in Python, Java, Scala, or similar language.
• Experience designing, developing, and operating production-grade services or distributed data-processing systems.
• Strong experience with AWS services and cloud-native architecture.
• Experience with Big Data technologies such as Spark/EMR and similar frameworks.
• Ability to solve complex technical problems independently.
• Experience owning a project or major technical component from design through production delivery.
• Solid understanding of software design, APIs, automated testing, CI/CD, and ops practices.
• Experience with performance, scalability, reliability, and load-testing.
• Ability to explain complex concepts and influence engineers and stakeholders.

Responsibilities

• Translate complex business and AI/ML requirements into scalable system designs and production-ready solutions.
• Lead end-to-end delivery of cloud, Big Data, and ML infrastructure projects from requirements to deployment.
• Design and develop distributed data pipelines and workflow orchestration using Spark, EMR, S3, Metaflow, AWS Batch, Step Functions, and Fargate.
• Build reusable platform capabilities so data scientists and product teams can deploy AI/ML workflows efficiently.
• Exercise independent judgment when selecting architectures, frameworks, testing strategies, and evaluation criteria.
• Improve platform reliability, scalability, observability, security, and cost efficiency through analysis and architectural enhancements.
• Develop automated, integration, scale, and load tests for production-level workloads.
• Collaborate with data scientists, software engineers, product managers, and platform teams to align technical execution with business priorities.
• Define development practices, review designs and code, and communicate new methods to the project team.
• Provide technical guidance, coaching, and feedback to junior engineers while collaborating with senior leaders.
• Own major technical initiatives, plan work, coordinate dependencies, and review deliverables.
• Participate in architectural discussions and influence long-term technical direction of data and ML platforms.

Skills

Python

Java

Scala

AWS

Big Data

Distributed data processing

CI/CD

Mentoring

Problem solving

Education

Bachelor’s degree in computer science, engineering, or related technical discipline

Tools

Spark

EMR

S3

Metaflow

AWS Batch

Step Functions

Fargate

Terraform

CloudFormation

Job description

Be the one building AI-powered experiences where they matter most

At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.

Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.

Role Overview

We are seeking a Senior Software Engineer to design and build scalable cloud, Big Data, and machine-learning infrastructure that powers AI-driven Workforce Management capabilities. This role offers the opportunity to solve complex distributed-systems problems, lead projects from design through production, and build reusable platforms that accelerate AI/ML development across multiple teams.

The ideal candidate combines strong software-engineering fundamentals with experience in AWS, distributed data processing, and production platform development. They will influence technical direction, mentor other engineers, and help improve the scalability, reliability, observability, and cost efficiency of our data and ML systems.

Key Responsibilities

• Translate complex business and AI/ML requirements into scalable system designs, technical plans, and production-ready solutions.
• Lead the end-to-end delivery of cloud, Big Data, and ML infrastructure projects from requirements and architecture through testing, deployment, and operational support.
• Design and develop distributed data pipelines and workflow-orchestration services using technologies such as Spark, EMR, S3, Metaflow, AWS Batch, Step Functions, and Fargate.
• Build reusable platform capabilities that enable data scientists and product teams to develop, deploy, and operate AI/ML workflows efficiently.
• Exercise independent judgment when selecting architectures, frameworks, testing strategies, and evaluation criteria for complex technical problems.
• Improve platform reliability, scalability, observability, security, and cost efficiency through performance analysis and architectural enhancements.
• Develop automated, integration, scale, and load tests to validate systems under production-level workloads.
• Collaborate with data scientists, software engineers, product managers, and platform teams to align technical execution with business priorities.
• Define development practices, review technical designs and code, and communicate new methods and procedures to the broader project team.
• Provide technical guidance, coaching, and constructive feedback to junior engineers while learning and collaborating with senior technical leaders.
• Own major technical initiatives, including planning work, coordinating dependencies, delegating tasks when appropriate, and reviewing deliverables.
• Participate in architectural discussions and influence the long-term technical direction of the team’s data and ML platforms.

Minimum Requirements

• Five or more years of relevant professional software-engineering experience, or equivalent experience supported by an advanced degree.
• Advanced programming experience in Python, Java, Scala, or a comparable language.
• Experience designing, developing, and operating production-grade services or distributed data-processing systems.
• Strong experience with AWS services and cloud-native architecture.
• Experience with Big Data technologies such as Apache Spark, EMR, or similar distributed-processing frameworks.
• Demonstrated ability to independently solve complex and ambiguous technical problems.
• Experience owning a project or major technical component from initial design through production delivery.
• Strong understanding of software design, APIs, automated testing, CI/CD, and operational support practices.
• Experience with performance, scalability, reliability, and load-testing methodologies.
• Ability to explain complex technical concepts and influence engineers and internal stakeholders.
• Demonstrated experience mentoring, coaching, reviewing, or providing technical guidance to other engineers.
• Bachelor’s degree in computer science, engineering, or a related technical discipline, or equivalent practical experience.

Desirable Skills

• Experience with ML platforms, MLOps, model deployment, or AI/ML workflow orchestration.
• Experience with Metaflow, Airflow, Kubeflow, or comparable workflow-management frameworks.
• Experience with AWS Batch, ECS/Fargate, Step Functions, Lambda, DynamoDB, SQS, and Aurora.
• Experience designing secure multi-account or multi-tenant AWS architectures.
• Familiarity with infrastructure-as-code tools such as Terraform, AWS CDK, or CloudFormation.
• Experience implementing observability using CloudWatch, OpenTelemetry, New Relic, or similar platforms.
• Experience optimizing cloud infrastructure for performance and cost.
• Familiarity with workforce management, forecasting, anomaly detection, or Agentic AI applications.

Compensation

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. This role might also be eligible for a commission or performance-based bonus opportunities.

$124,600.00 - 163,600.00

Working at Genesys

• AI at enterprise scale – Build, support and operate AI-powered technology used by more than 8,000 organizations worldwide. 150+ new AI features were released in the last fiscal year
• A flexible-first culture – Join a global team of nearly 7,000 employees with flexible ways of working designed to help people do their best work
• Growth in the AI era – Build future-ready skills through mentorship, learning programs, leadership development and education support
• Time to recharge and give back – Benefits include paid volunteer time, August Free Fridays, well-being resources and regionally tailored programs for employees and their families
• Recognized globally – Genesys is Great Place to Work® certified in 17 countries and 94% of employees are proud to tell others they work at Genesys

Learn more about our culture, AI innovation and sustainability commitments through our Careers site and Sustainability Report.

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About Genesys

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud™ is the AI-Powered Experience Orchestration platform that connects people, systems, data and AI across the enterprise. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit www.genesys.com.

Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.

Please note that recruiters will never ask for sensitive personal or financial information during the application phase.