Product Architect – Enterprise Analytics Services

Ralliant

$110K — $140K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years in enterprise software engineering
  • Experience with C#/.NET and C++
  • Expertise in distributed systems and Kubernetes
  • Proficient in cloud-native development and cybersecurity
  • Knowledgeable in Agile/SAFe practices and specification-driven AI-first engineering

Responsibilities

  • Own product architecture and develop the technical roadmap
  • Lead specification reviews and make architectural decisions
  • Utilize AI-assisted engineering tools for efficient software delivery
  • Promote platform reuse and API-first design
  • Mentor Product Engineers and collaborate with QA and Product Owners

Benefits

  • Work within an Agile Scrum framework
  • Engage in daily collaboration with Product Owners and fellow engineers
  • Focus on delivering secure, observable software across multiple cloud platforms
  • Align with principles of security and observability as core product elements
Full Job Description
JOB DESCRIPTION

Product Architect – Enterprise Analytics Services

Position Summary

Technical architecture leader for a product squad responsible for translating product vision into executable architecture and production software.

Mission

Lead architecture for one Enterprise Analytics product domain while mentoring engineers and ensuring alignment with QualCore platform standards.

Areas of Stewardship
  • Own product architecture and technical roadmap.
  • Lead specification reviews and architectural decisions.
  • Use AI-assisted engineering tools to accelerate production-quality software delivery while maintaining human accountability. 
  • Drive platform reuse and API-first design.
  • Coach Product Engineers and partner with QA and Product Owners.
What You'll Bring

8+ years in enterprise software engineering with architecture experience, C#/.NET, C++, distributed systems, Kubernetes, cloud-native development, cybersecurity, observability, Agile/SAFe, and specification-driven AI-first engineering.

Ways of Working

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

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.

 

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