AI Engineer

Planet; Porto; Híbrido; EUR 55 000 - 90 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work model

Resumo da oferta

Planet is seeking an engineer to design and deliver production AI workflows that automate and augment internal processes across HR, Finance, Operations and CRM.

You will build AI agents, prompts, and retrieval pipelines while ensuring reliability, auditability, and measurable impact on decision quality.

Qualificações

• Strong software engineering background with production systems experience.
• Hands-on experience with AI/ML systems (LLMs, classifiers, decision models).
• Experience integrating APIs and working with distributed systems.

Responsabilidades

• Design and build production-grade AI workflows across internal systems (HR, Finance, Operations, CRM).
• Implement orchestration logic: triggers, retries, fallbacks, human-in-the-loop patterns.

Conhecimentos

Software engineering

Python

AI/ML systems

APIs

Distributed systems

Ambiguity handling

Ferramentas

Temporal

Airflow

Step Functions

Descrição da oferta de emprego

About Planet

Planet is a global provider of integrated technology and payments solutions for retail and hospitality customers.

About Planet

Planet is a global provider of integrated technology and payments solutions for retail and hospitality customers.

We create great experiences for the millions of people who use our payments, software, and tax-free solutions every minute of every day.

Planet empowers its customers to deliver great customer experiences by combining payments and software in ways that drive greater loyalty, increase revenue and save time.

Founded over 35 years ago and with our headquarters in London, today we have more than 2,500 employees located across six continents serving our customers in more than 120 markets.

Role Overview

This role owns the design, delivery, and ongoing behaviour of production AI workflows that automate and augment work across Planet’s internal systems — HR, Finance, Operations, and CRM. You will be accountable not only for shipping the technology, but for the quality of the decisions it makes: building agents, prompts, and retrieval pipelines that business users can trust, and improving them over time through measurement and real-world feedback. The impact is direct — reliable, auditable AI that reduces manual effort and raises the quality and speed of everyday decisions across the business.

What You Will Do

• Design and build production-grade AI workflows that integrate across internal systems (HR, Finance, Operations, CRM).
• Implement the orchestration logic — triggers, retries, fallbacks, and human-in-the-loop patterns — so workflows run reliably, observably, and auditably.
• Develop and maintain the AI agents, prompts, retrieval pipelines, and decision logic that power those workflows.
• Own model behaviour in production: accuracy and usefulness, failure modes, and edge-case and ambiguity handling.
• Iterate on model performance using evaluation frameworks, feedback loops, and real-world usage data.
• Take accountability for decision quality and outcomes — not just technical execution — defining and tracking success metrics such as accuracy, resolution rate, and time saved.
• Diagnose cases where systems are technically “working” but producing poor outcomes, and close the gap.
• Partner with Data Engineering on shared platforms (infrastructure, CI/CD, data pipelines, security and governance) and contribute to shared standards, schemas, and best practices for AI systems.
  
  

Who You Are

• Strong software engineering background (Python or similar), with a track record of building production systems — not just prototypes.
• Hands-on experience with AI / ML systems (LLMs, classifiers, decision models, or similar).
• Experience integrating APIs and working with distributed systems.
• Experience designing prompts, retrieval pipelines, or ML inference workflows.
• Solid understanding of model evaluation, monitoring, and feedback loops; comfortable working with both structured and unstructured data.
• Product-oriented — cares about outcomes, not just shipping code; pragmatic about AI and focused on what works in production.
• Comfortable owning ambiguity and making trade-offs.
• Languages: English
• A plus, but not required: workflow orchestration tools (Temporal, Airflow, Step Functions); experience building internal tools or agents; familiarity with regulated or enterprise environments; exposure to MLOps or AI evaluation frameworks.
  
  

Why Planet

Planet is an equal opportunity employer where diversity is valued, and all employment is decided based on qualifications, merit, and business need.

Come and grow your career in the most exciting, fast paced technology market, with a business that delivers feel-good connected commerce.

At Planet, we embrace a hybrid work model, with three days a week in the office.

Reasonable accommodations may be made in order to allow for an individual to perform the essential functions of this role successfully.