Senior AI Platform Engineer

Aimlroles; Lisboa; On-site; EUR 70,000 - 110,000; Full time

Job summary

Chain IQ in Lisbon is seeking a senior software engineer to design, deploy, and operate production AI capabilities within an AI-native procurement platform.

You will build deployment pipelines, evaluation frameworks, and observability across models, retrieval systems, and AI agents, working with ML, Platform Eng, Product Eng, and Data Eng teams to ensure reliability and scalability.

Qualifications

• Experience operating production ML/AI platforms.
• Strong software engineering skills with automation and tooling.
• Exposure to cloud-native infra, containers, and distributed systems.

Responsibilities

• Design, build, and maintain platform capabilities to deploy and operate production AI systems.
• Develop automated pipelines for model packaging, deployment, versioning, testing, rollout, and lifecycle management.
• Build evaluation frameworks measuring model quality, retrieval effectiveness, latency, cost, and business performance.
• Implement monitoring for models, inference services, retrieval pipelines, and AI agents.

Skills

Production ML/AI platforms experience

Software engineering

CI/CD

Observability

Cloud-native infrastructure

Container platforms

Tools

Kubernetes

Terraform

Docker

Job description

At Chain IQ, your ideas move fast.

Chain IQ is a global AI-driven Procurement Service Partner, headquartered in Baar, Switzerland, with operations across main centers and 16 offices worldwide. We provide tailored, end-to-end procurement solutions that enable transformation, drive scalability, and deliver substantial reductions in our clients’ indirect spend. Our culture is built on innovation, entrepreneurship, ownership, and impact. Here, your voice matters - bold thinking is encouraged, and action follows ambition.

Role purpose

We are building an AI-native procurement platform where machine learning models, retrieval systems, AI agents, and intelligent applications operate as production services. This role is responsible for ensuring those capabilities can be deployed, monitored, evaluated, and continuously improved at enterprise scale.

You will build the engineering capabilities that take AI from experimentation into reliable production systems. This includes model deployment, inference infrastructure, evaluation pipelines, observability, versioning, performance monitoring, and automation across the AI lifecycle. You will work closely with Machine Learning, Platform Engineering, Product Engineering, and Data Engineering to ensure AI capabilities remain scalable, secure, and operationally robust.

This is a senior engineering role requiring strong software engineering, cloud platform, and operational experience combined with practical knowledge of modern AI deployment practices.

Why this role matters

Reliable AI products require more than high-performing models. They depend on robust platforms that support continuous deployment, evaluation, monitoring, and improvement throughout the AI lifecycle. This role is critical in ensuring AI capabilities are delivered with the same reliability, scalability, and engineering discipline as the broader technology platform, enabling teams to innovate quickly while maintaining quality, resilience, and trust in production environments.

Responsibilities

• Design, build, and maintain the platform capabilities required to deploy and operate production AI systems.
• Develop automated pipelines for model packaging, deployment, versioning, testing, rollout, rollback, and lifecycle management.
• Build evaluation frameworks that continuously measure model quality, retrieval effectiveness, latency, cost, and business performance.
• Implement monitoring for models, inference services, retrieval pipelines, and AI agents using metrics, logging, tracing, and operational telemetry.
• Partner with Machine Learning Engineers to productionize models and improve deployment reliability.
• Collaborate with Platform Engineering to optimise runtime environments, infrastructure, scaling, security, and operational resilience.
• Develop deployment strategies supporting experimentation, canary releases, A/B testing, and progressive rollouts.
• Implement governance controls supporting reproducibility, version management, auditability, and operational compliance.
• Automate repetitive operational activities wherever possible, improving engineering productivity and deployment confidence.
• Contribute to the evolution of the Agentic Software Development Lifecycle (ASDLC) by embedding evaluation, automation, and operational intelligence into AI delivery processes.

Requirements

• Experience operating production machine learning or AI platforms.
• Software engineering skills with experience building automation, deployment pipelines, and operational tooling.
• Exposure to cloud-native infrastructure, container platforms, and distributed systems.
• Deep understanding of CI/CD, infrastructure as code, release automation, and production operations.
• Strong capability implementing observability across complex distributed applications.
• Understanding of model lifecycle management, deployment strategies, experimentation, and production evaluation.
• Track record collaborating across Platform Engineering, Machine Learning, Product Engineering, and Data Engineering teams.
• Analytical and troubleshooting skills with a focus on reliability, operational excellence, and continuous improvement.
• Ability to simplify operational complexity through automation and reusable platform capabilities.

Join a truly global team.

We offer a dynamic and international environment where high performance meets real purpose. We're proud to be Great Place to Work-certified and even prouder of the people who make that possible. Let’s shape the future of procurement - together.

Chain IQ – Create. Lead. Make an impact.