AI Engineer

Planet Paymet; Porto; Presencial; EUR 60 000 - 100 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work model

Reasonable accommodations

Resumo da oferta

Planet seeks a production-focused AI workflow engineer to design and deliver AI-powered processes across HR, Finance, Operations, and CRM. You will build agents, prompts, and pipelines, ensuring reliable, auditable decisions and measurable improvements in accuracy and speed.

Strong Python skills and API integration experience are essential. You will own model behaviour in production, address edge cases, and collaborate with Data Engineering to maintain robust infrastructure, CI/CD, and data

Qualificações

• Strong software engineering background (Python or similar).
• Hands-on experience with AI/ML systems (LLMs, classifiers, inference).
• Experience integrating APIs and distributed systems.
• Experience designing prompts or retrieval pipelines for ML workflows.
• Solid understanding of model evaluation, monitoring and feedback loops.
• Product-focused mindset, production readiness and pragmatic AI decisions.

Responsabilidades

• Design and build production-grade AI workflows across internal systems (HR, Finance, Ops, CRM).
• Implement orchestration logic (triggers, retries, fallbacks, human-in-the-loop).
• Develop and maintain AI agents, prompts, and retrieval pipelines.
• Own model behaviour in production: accuracy, failure modes, edge cases.
• Iterate on model performance with evaluation frameworks and real-world data.
• Define and track success metrics (accuracy, resolution rate, time saved).
• Collaborate with Data Engineering on infrastructure, CI/CD, data pipelines, security and governance.

Conhecimentos

Software engineering

Python

AI/ML systems

APIs & distributed systems

Prompts & retrieval pipelines

Model evaluation & monitoring

Product-focused

Production-grade systems

Ferramentas

CI/CD

Data pipelines

Descrição da oferta de emprego

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.

Company Background

Planet provides integrated software, payment and technology solutions for its customers in the Hospitality and Retail sectors and worldwide via a network of global Financial Services Partners. Founded over 35 years ago, we have evolved our services, delivering an innovative digital commerce platform that puts customer experience first. With headquarters in London and around 3,000 expert employees located across six continents we serve customers in over 120 markets.