Product Engineer – Analytics as a Service

The Product Engineer is responsible for rapidly designing building and delivering cloud-native analytics services that create measurable customer value. The engineer will operate as a full-stack product builder rather than traditional software developers owning features from concept through production.

Working alongside the Product Owner and SaaS Architect the Product Engineer will leverage AI-assisted specification-driven development practices to accelerate delivery while maintaining exceptional software quality. The engineer is expected to iterate quickly with customers continuously improve the platform and contribute across the full software lifecycle.

This role is intended for builders who thrive in high-growth fast-paced environments where speed ownership and customer impact are equally important.

Design develop and maintain cloud-native analytics services.

Deliver production-ready software across:

• Backend services
• APIs
• Data pipelines
• User interfaces
• Cloud infrastructure
• Analytics capabilities

Use AI extensively to accelerate:

• software design
• specification refinement
• coding
• unit testing
• integration testing
• documentation
• troubleshooting
• code reviews

Continuously improve engineering productivity through AI-enabled development practices.

Work closely with Product Owner and Customer Success to:

• understand customer needs
• validate assumptions
• prototype rapidly
• incorporate customer feedback
• deliver frequent releases

Maintain direct awareness of customer outcomes rather than simply completing development tasks.

Build software that is:

• Secure
• Reliable
• Observable
• Maintainable
• Well-tested
• Highly scalable

Participate in architecture discussions peer reviews and continuous improvement initiatives.

Partner closely with:

• Product Owner
• SaaS Architect
• DevOps
• Customer Success
• Commercial Leader

Contribute to a collaborative high-performance engineering culture focused on rapid execution and continuous learning.

• 5 years professional software development
• Experience developing SaaS applications
• Experience with cloud-native architectures
• Strong full-stack development skills
• Experience with Agile software delivery
• Experience working in fast-paced product organizations

Experience with:

• Microsoft Azure
• AWS
• Kubernetes
• Modern web frameworks
• Distributed systems
• Industrial IoT
• Data analytics platforms
• AI-assisted software development

Within 12 months:

• Consistently deliver high-quality production features
• Maintain rapid release cadence
• High automated test coverage achieved
• AI-assisted development practices fully adopted
• Strong customer adoption of delivered capabilities
• Active contribution to continuous platform improvement

Approximately 10% travel including periodic customer visits to strengthen product understanding.

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