Product Engineer – Enterprise Analytics Services

Ralliant

• $90K — $130K *
Rochester, NY 14609Hybrid
Enterprise Technology
5 - 7 years of experience
Today
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Job Overview by Ladders

Qualifications

  • 6+ years of experience in enterprise software development
  • Proficient with cloud-native architectures and event-driven systems
  • Experience in APIs, plugins, and testing automation
  • Familiar with Agile methodologies and AI-assisted engineering workflows
  • Strong background in software quality assurance

Responsibilities

  • Lead the implementation of significant software development projects
  • Create and author detailed engineering specifications
  • Design robust, distributed services for analytics
  • Ensure high standards of software quality through testing and production readiness
  • Mentor and guide junior Product Engineers

Benefits

  • Collaborative Agile team environment
  • Opportunity to mentor and grow technical skills
  • Focus on secure and cloud-agnostic enterprise software
  • Emphasis on architectural responsibility across teams
  • Engagement with AI technologies to enhance engineering workflows
Full Job Description
JOB DESCRIPTION

Product Engineer – Enterprise Analytics Services

Position Summary

Independent technical leader delivering complex software capabilities while contributing to architecture and mentoring peers.

Mission

Own delivery of complex analytics services from specification through production deployment.

Areas of Stewardship

  • Lead implementation of major epics.

  • Author engineering specifications.

  • Design resilient distributed services.

  • Drive software quality, testing, and production readiness.

  • Mentor Product Engineers.

What You'll Bring

6+ years building enterprise software, cloud-native development, APIs, event-driven systems, plugins, testing automation, Agile, and AI-assisted engineering workflows.

Ways of Working

Work within Agile Scrum teams using SAFe 6.0 principles. Collaborate daily with Product Owners, Product Architects, Quality Assurance, fellow engineers, and AI agents to deliver secure, observable, cloud-agnostic enterprise software.

Engineering Principles

  • Own products, not features.

  • Begin with specifications, not code.

  • AI accelerates engineering; accountability remains human.

  • Architecture is everyone's responsibility.

  • Design once. Deploy anywhere.

  • Security is a design requirement.

  • Observability is a product capability.

  • Optimize for customer outcomes.

* Ladders Estimates

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