Backend engineer building AI - powered 3D design review systems for CoLab, which helps mechanical engineering teams bring complex products to market faster. Developing scalable CAD, ML, and rule - based review infrastructure.
About the role
- Senior Software Engineer building scalable AWS, Big Data, and ML infrastructure for Genesys’ AI-powered customer-experience platform. Leading distributed systems projects from architecture through production.
Responsibilities
- Translate complex business and AI/ML requirements into scalable system designs, technical plans, and production-ready solutions
- Lead 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
- Build reusable platform capabilities enabling data scientists and product teams to develop, deploy, and operate AI/ML workflows
- Select 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
- Collaborate with data scientists, software engineers, product managers, and platform teams
- Define development practices, review technical designs and code, and communicate new methods and procedures
- Provide technical guidance, coaching, and feedback to junior engineers
- Own major technical initiatives, coordinate dependencies, delegate tasks, and review deliverables
- Participate in architectural discussions and influence the long-term technical direction of data and ML platforms
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
- 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
- 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
- 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 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
Benefits
- Flexible ways of working
- Mentorship, learning programs, leadership development and education support
- Paid volunteer time
- August Free Fridays
- Well-being resources
- Regionally tailored programs for employees and their families
- Potential eligibility for commission or performance-based bonus opportunities
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