Product Engineer – Analytics as a Service
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Product Engineer – Analytics as a Service
Location
Rochester, NY, United States
Experience
Mid
Posted
Jul 22, 2026
Apply by
August 21, 2026
Applicants
0
Early applicantEasy applyFull-timeHybrid
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 Responsibilities
### Product 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.
#LW-PW1
### About the Team
About Qualitrol
QUALITROL manufactures monitoring and protection devices for high value electrical assets and OEM manufacturing companies. Established in 1945, QUALITROL produces thousands of different types of products on demand and customized to meet our individual customers’ needs. We are the largest and most trusted global leader for partial discharge monitoring, asset protection equipment and information products across power generation, transmission, and distribution. At Qualitrol, we are redefining condition-based monitoring.
We Are an Equal Opportunity Employer
Ralliant Corporation and all Ralliant Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Ralliant and all Ralliant Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at applyassistance@Ralliant.com.
### About the Company
Ralliant Corporation Overview
Ralliant, originally part of Fortive, now stands as a bold, independent public company driving innovation at the forefront of precision technology. With a global footprint and a legacy of excellence, we empower engineers to bring next-generation breakthroughs to life — faster, smarter, and more reliably. Our high-performance instruments, sensors, and subsystems fuel mission-critical advancements across industries, enabling real-world impact where it matters most. At Ralliant we’re building the future, together with those driven to push boundaries, solve complex problems, and leave a lasting mark on the world.
Key Responsibilities
- Design, develop, and maintain cloud-native analytics services including backend services, APIs, data pipelines, and user interfaces.
- Leverage AI-assisted practices to accelerate software design, coding, testing, and documentation.
- Collaborate with Product Owners and Customer Success to understand needs, validate assumptions, and incorporate feedback.
- Build secure, reliable, observable, and scalable software with high automated test coverage.
- Partner with DevOps, SaaS Architects, and other engineering teams to contribute to a high-performance culture.
Skills Required
Cloud-native architecturesFull-stack developmentSaaS application developmentAgile software deliveryCustomer-centric engineeringTeam collaborationRapid executionContinuous learningMicrosoft AzureAWSKubernetesModern web frameworksDistributed systemsIndustrial IoTData analytics platformsAI-assisted software development
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