Product Engineer – Analytics as a Service

Ralliant

$90K — $120K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of professional software development experience
  • Proven ability to develop SaaS applications
  • Familiarity with cloud-native architectures
  • Strong full-stack development capabilities
  • Experience in Agile software delivery
  • Background in fast-paced product organizations

Responsibilities

  • Design, develop, and maintain cloud-native analytics services
  • Deliver production-ready software across backend services, APIs, and user interfaces
  • Leverage AI to enhance software design, coding, and testing
  • Engage directly with customers to understand needs and gather feedback
  • Ensure high standards of software quality including security and scalability
  • Collaborate with various stakeholders to foster a high-performance engineering culture

Benefits

  • Opportunity to work in a high-growth, fast-paced environment
  • Focus on rapid execution and continuous learning
  • Involvement in an innovative AI-assisted development process
  • Emphasis on customer impact and satisfaction
  • Engagement with a collaborative team of experts
  • Flexible travel opportunities for customer interaction
Full Job Description
JOB DESCRIPTION
Product Engineer – Analytics as a Service 

Position Summary

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.

Primary ResponsibilitiesProduct Development

Design, develop and maintain cloud-native analytics services.

Deliver production-ready software across:

  • Backend services
  • APIs
  • Data pipelines
  • User interfaces
  • Cloud infrastructure
  • Analytics capabilities
AI-First Development

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.

Customer-Centric Engineering

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.

Engineering Quality

Build software that is:

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

Participate in architecture discussions, peer reviews and continuous improvement initiatives.

Team Collaboration

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.

Required Experience
  • 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
Preferred Experience

Experience with:

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

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
Travel

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

 

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