AI Platform Engineer

Job not on LinkedIn

🕒 August 29

🇩🇪 Germany – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 19%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Deluxe

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1915

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Deluxe is a leading financial services technology company that specializes in payment processing and data solutions. With over 100 years of experience, it connects small businesses, financial institutions, and major brands through a comprehensive suite of payment methods and financial services. Deluxe processes over $3 trillion in payment volume annually, offering tools for receivables, payables, and marketing, aimed at helping businesses grow and manage their finances efficiently.

📋 Description

• Build and operate platforms for deploying, monitoring, and maintaining production AI models and services • Support model-serving environments, inference pipelines, deployment workflows, and release automation • Develop automation for model packaging, promotion, validation, rollout, rollback, and lifecycle management • Implement monitoring, logging, alerting, and observability for AI services, including performance, latency, availability, error rates, and cost • Partner with AI Engineers to move models, workflows, and AI services from prototype to production • Partner with cloud platform, infrastructure, and application teams to ensure AI services run on secure, scalable, and reliable environments • Help define operational standards for production AI systems, including runbooks, incident response, testing, and release readiness • Support batch and real-time AI workloads where applicable • Troubleshoot issues related to model serving, API behavior, environment configuration, infrastructure, and deployment pipelines • Build reusable patterns for AI service deployment and integration across Deluxe applications • Contribute to evaluation and adoption of MLOps tools, model-serving frameworks, observability platforms, and AI infrastructure technologies

🎯 Requirements

• Experience in MLOps, AI platform engineering, DevOps, software engineering, or production ML operations • Experience deploying or operating AI/ML models, inference services, data services, or API-based production systems • Strong scripting or programming skills using Python or similar languages • Experience with containers, CI/CD, cloud environments, monitoring, and operational automation • Understanding of model deployment concepts, model lifecycle management, versioning, validation, and rollback • Experience troubleshooting production systems across application, model, infrastructure, and deployment layers • Preferred: Experience with model-serving frameworks, MLOps platforms, Kubernetes, Docker, ECS, EKS, MLflow, KServe, BentoML, Ray, Airflow, or similar technologies • Preferred: Experience supporting LLMs, agentic workflows, RAG systems, speech models, translation models, or other applied AI services • Preferred: Experience with GPU-backed inference, batch processing, distributed systems, or high-throughput workloads • Preferred: Experience with AWS services used for compute, storage, networking, security, monitoring, and deployment • Preferred: Experience with media, localization, dubbing, content workflows, ASR, MT, TTS, or language technologies • Preferred: Experience evaluating or integrating commercial and open-source AI platforms