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Open nowPosted 3 days ago

Product Engineer

ambi.26 open roles

Pay
€110,000 – €160,000 a yearly
Where
Lisbon, Portugal
Work mode
Hybrid
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Your applicationOpen nowProduct Engineerambi. · Lisbon, Portugal
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Early applications get read.

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Share of postings closed within
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  2. 4.2%3 days
  3. 11.4%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 3 days ago

The posting

The Role

Build products that solve real customer problems—and own them from the first idea to production.

As a Product Engineer, you’ll work across the full stack, connecting technical decisions to customer outcomes. You’ll turn ambiguous requirements into focused releases, ship quickly, and use feedback and measurable results to decide what comes next.

You’ll also work directly with enterprise customers to understand their workflows and deliver features that make a difference. You should be comfortable asking questions and explaining your decisions; polished presentation skills aren’t a prerequisite.

Experience in retail or consumer packaged goods (CPG) isn’t required. Curiosity about how customers’ businesses work is.

What You’ll Do

  • Own features end to end. Take responsibility for the interface, APIs, data, deployment, and performance in production.
  • Turn ambiguity into action. Identify the customer problem, define a practical scope, and ship a useful first version within a week.
  • Make product decisions. Define what success looks like, evaluate results, and change direction or stop work when it isn’t delivering value.
  • Build with AI. Use coding agents and other AI tools to accelerate development while remaining accountable for code quality, testing, and reliability.
  • Deliver a thoughtful user experience. Pay attention to how features look, feel, and behave, and resolve the details that make them easier to use.
  • Collaborate early. Work closely with product, design, and engineering, bringing in the right people when you need context or expertise.

What You’ll Bring

These are the core capabilities we’ll assess throughout the hiring process:

  • A track record of shipping. You’ve repeatedly taken features from unclear requirements to production across the full stack. You can make progress independently and take ownership of the outcome.
  • Strong product judgement. You can scope an MVP, choose a meaningful success metric, and explain the trade-offs between speed and depth. You can describe the value your work created for customers or the business.
  • An AI-native approach to development. You use AI tools daily, including coding agents such as Claude Code or Codex, and can coordinate multiple agents when useful. You critically review their output and own the quality of the final result, including AI-generated tests and reviews.
  • An eye for quality. You notice confusing interactions, inconsistent interfaces, and rough edges—and take the initiative to fix them.
  • Effective collaboration. You communicate clearly across functions, seek missing context early, and help others move forward.

Additional Experience We’d Value

  • Designing and operating distributed systems, with sound judgement around scalability, security, and reliability.
  • Shipping LLM-powered features or AI agents, including structured response handling and human-in-the-loop workflows.
  • Building production AI systems with evaluations, prompt engineering, safety controls, and cost optimisation.
  • Designing interfaces for AI-assisted workflows, including confidence signals and opportunities for users to review or intervene.

This role focuses on building products with AI, rather than training models.

Who Will Thrive Here

You’ll enjoy this role if you like working independently, learning through direct customer contact, and balancing speed with thoughtful execution. You should want to own the complete feature journey, with hands-on work across both frontend and backend.

Tech Stack

  • Languages and frameworks: TypeScript, Next.js, React, Tailwind CSS, Fastify
  • Data and validation: PostgreSQL, Kysely, Zod
  • Cloud and observability: Google Cloud Platform, Datadog
  • AI: Anthropic models and tooling

You don’t need experience with every part of the stack. You do need strong fundamentals and the ability to learn quickly.

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