quintegro

Product Engineer

Location: Remote

Quintegro builds digital products for US-based clients ranging from startups to Fortune 500 companies. We operate as embedded product and engineering partners — owning the full lifecycle from product strategy and discovery through design, engineering, QA, DevOps, CI/CD, launch, and long-term evolution.

We are also an innovation partner for organizations that need to move faster than traditional internal teams allow: validating ideas, building MVPs, accelerating delivery with AI, and creating scalable product systems.

Our delivery model is built around small, autonomous Pods — cross-functional teams that combine human expertise with modern AI tooling and agentic workflows.


Each Pod typically includes:

  • Intent Manager — owns business outcomes, stakeholder alignment, product direction, and success measurement
  • Product Engineer — full-cycle builder responsible for implementation, systems thinking, and AI-accelerated delivery
  • Architect — responsible for system architecture, platform scalability, technical standards, security, reliability, and long-term maintainability
  • Designer — shapes user experience, interaction flows, and product clarity
  • QA — owns quality strategy, validation systems, and reliability

We believe modern product development is no longer about managing tickets across silos. It is about high-agency teams using AI effectively to reduce friction, compress feedback loops, and maximize customer impact.

We intentionally structure Pods so that every role remains partially hands-on in building products. Intent Managers prototype and validate ideas directly in code and AI tools, Designers contribute through interactive systems and AI-assisted workflows, QA engineers automate and extend validation systems, and Architects actively shape implementation decisions alongside Product Engineers.

If you thrive in ambiguity, think in systems, communicate clearly with both business and technical stakeholders, and want to help redefine product management in the age of AI-assisted software development — we’d love to talk.

About the Role

The Product Engineer is the primary builder inside the Pod.

This role combines software engineering, product thinking, systems design, delivery ownership, and AI-native development practices.

Unlike traditional engineering roles organized around narrowly scoped frontend or backend responsibilities, Product Engineers at Quintegro own features and product outcomes end-to-end:

  • understanding user intent,
  • collaborating directly with stakeholders,
  • shaping technical approaches,
  • implementing across the stack,
  • validating quality,
  • deploying to production,
  • and iterating based on real-world feedback.

We are intentionally building a new type of engineering culture optimized for AI-first software development.

That means Product Engineers are expected to:

  • work effectively across technologies and abstraction layers,
  • leverage AI agents and automation aggressively,
  • operate with high autonomy,
  • and continuously improve delivery systems and workflows.

The ideal candidate is a strong builder who cares equally about product outcomes, engineering quality, execution speed, and learning velocity.

What You’ll Do

Own Features End-to-End

  • Take full ownership of features and product capabilities from concept to production
  • Work directly with Intent Managers, Designers, Architects, QA, and stakeholders to clarify requirements and shape solutions
  • Build across the stack rather than operating within narrow frontend/backend silos
  • Make pragmatic technical decisions aligned with business goals and delivery constraints
  • Deploy, monitor, iterate, and continuously improve shipped functionality
  • Participate in discovery, prototyping, implementation, testing, rollout, and post-launch optimization

Build Using AI-First Engineering Practices

  • Use modern AI tools as a core part of daily engineering workflows
  • Apply spec-driven development practices to improve clarity, reduce ambiguity, and accelerate implementation
  • Work with multi-agent development workflows for planning, implementation, validation, refactoring, debugging, testing, and documentation
  • Use AI-assisted code generation, code review, analysis, migration, and troubleshooting responsibly and effectively
  • Continuously refine prompts, workflows, context management, and automation systems to improve engineering throughput and quality
  • Treat AI systems as collaborative engineering infrastructure rather than simple autocomplete tools

Operate Across Technologies & Systems

  • Work comfortably across APIs, databases, frontend systems, infrastructure, integrations, automations, and cloud environments
  • Navigate unfamiliar technologies quickly with the help of AI-assisted workflows and strong engineering fundamentals
  • Contribute to architecture, reliability, security, performance, observability, and maintainability discussions
  • Help improve development tooling, internal platforms, CI/CD systems, and engineering processes

Build High-Quality Production Systems

  • Write clean, maintainable, well-structured production code
  • Validate functionality through testing, instrumentation, and observability practices
  • Collaborate closely with QA to ensure reliability and production readiness
  • Participate in debugging, incident resolution, and operational improvements
  • Balance delivery speed with long-term system quality and maintainability

Contribute to Pod Effectiveness

  • Communicate clearly and proactively inside highly collaborative Pods
  • Help reduce ambiguity through strong technical communication and documentation
  • Stay in close, continuous communication with the Pod to keep context fresh, surface blockers early, and maintain shared ownership of delivery
  • Share knowledge, improve workflows, and contribute to engineering culture
  • Take initiative rather than waiting for narrowly scoped assignments

Engineering Practices We Care About

We continuously evolve our engineering workflows, but common patterns include:

  • Spec-driven development
  • AI-assisted architecture and implementation planning
  • Multi-agent engineering workflows
  • Rapid prototyping and iterative delivery
  • Lightweight specs, shared context, and decision capture that support fast execution without replacing active communication
  • AI-assisted testing and validation systems
  • Continuous refactoring and simplification
  • Infrastructure-as-code and automated environments
  • Strong observability and production feedback loops
  • Autonomous ownership with collaborative review

We are less interested in whether someone identifies as a “frontend engineer” or “backend engineer” and more interested in whether they can effectively build and ship valuable product capabilities

What We’re Looking For

Required

  • 5+ years of experience building production software systems
  • Strong software engineering fundamentals across multiple layers of modern applications
  • Ability to independently own and deliver product capabilities end-to-end
  • Experience working across different technologies, frameworks, APIs, databases, and cloud systems
  • Hands-on experience using modern AI tools in software development workflows
  • Strong problem-solving skills and ability to navigate ambiguity effectively
  • Excellent communication and collaboration skills in cross-functional teams
  • Ability to communicate with external development teams in English
  • Ability to learn new technologies and systems quickly
  • Comfort operating in fast-moving, low-bureaucracy environments with high ownership
  • Strong product mindset and ability to think beyond implementation details

Strong Plus

  • Experience in AI-native or AI-assisted engineering environments
  • Experience with agentic workflows, orchestration systems, AI coding assistants, or developer automation
  • Experience with DevOps, infrastructure, CI/CD, cloud systems, or platform engineering
  • Experience working in startups, agencies, consulting, or product-focused environments
  • Experience building scalable SaaS products or operational systems
  • Familiarity with observability, security, performance optimization, and reliability engineering
  • Previous technical leadership or architecture experience

How We Work

At Quintegro, we optimize for:

  • Small, autonomous teams
  • High ownership and accountability
  • Fast feedback loops
  • AI-accelerated execution
  • Pragmatic decision-making
  • Outcome-driven delivery
  • Continuous learning and experimentation


We value engineers who:

  • proactively solve problems,
  • communicate clearly,
  • think in systems,
  • embrace modern tooling,
  • and care deeply about building useful products.

What We Offer

  • Remote-first work environment with flexible hours and consistent working overlap across EST and CET time zones as part of collaborative Pod operations
  • High autonomy and meaningful ownership of product delivery
  • Opportunity to help shape modern AI-first engineering practices
  • Access to cutting-edge AI tools, cloud resources, and experimentation environments
  • Diverse technical challenges across startups and enterprise organizations
  • Collaborative engineering-first culture with highly capable peers
  • Competitive compensation and strong growth opportunities
  • A team that values craftsmanship, speed, curiosity, and continuous improvement

Excited to contribute to our mission? Join our team! Send your application to:

join.us@quintegro.comTo the List of Vacancies