Technical Product Owner - AI Platform (AWS & MLOps)

nexttech

14h

About The Position

We are looking for a Technical Product Owner to lead the evolution and delivery of modern AI platform capabilities built on cloud-native technologies and MLOps best practices. This is not a traditional product ownership role focused solely on requirements management. We are searching for a technically strong Product Owner who understands cloud architecture, AI infrastructure, and platform engineering, and who enjoys working closely with engineering teams to turn complex business needs into scalable technical solutions. The ideal candidate can effectively bridge business objectives and technical execution while driving the development of AI platforms that support machine learning, generative AI, and large-scale cloud workloads in a secure, reliable, and operationally efficient manner.

Requirements

At least 5+ years of experience as a Product Owner, Technical Product Manager, Solutions Architect, or similar technical leadership role.
Strong hands-on understanding of AWS services, including IAM, VPC, ECS/EKS, Lambda, S3, API Gateway, CloudWatch, and SageMaker.
Experience designing and delivering cloud infrastructure supporting AI and machine learning workloads.
Strong knowledge of MLOps principles, CI/CD pipelines, containerization, Kubernetes, and machine learning lifecycle management.
Hands-on experience with Infrastructure as Code approaches, particularly Terraform.
Good understanding of modern AI architectures, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and AI inference workloads.
Ability to translate complex technical concepts into clear business value and priorities.
Experience working in Agile/Scrum environments and managing technical product backlogs.
Strong communication and stakeholder management skills across both technical and non-technical audiences.
Experience balancing short-term delivery objectives with long-term platform strategy and scalability.
Strong expertise, a collaborative spirit, a responsible and diligent mindset, resilience, flexibility, open-mindedness, courage, and an innate desire to support your teammates.

Nice To Haves

AWS certifications.
Experience with MLflow, Kubeflow, Airflow, or similar MLOps and orchestration platforms.
Experience working with Azure or Google Cloud Platform (GCP).
Exposure to AI platform engineering, data platforms, or enterprise AI initiatives.
German language skills.

Responsibilities

Own and prioritize the product backlog for AI platform, cloud infrastructure, and MLOps initiatives.
Translate business requirements into technical specifications, epics, user stories, and platform capabilities.
Collaborate closely with engineering, DevOps, data, and AI teams to deliver scalable and reliable AI solutions.
Drive the definition and evolution of cloud architecture, deployment strategies, security standards, and operational best practices.
Support the design and implementation of AI platform capabilities enabling model training, deployment, monitoring, and lifecycle management.
Establish and continuously improve MLOps processes, automation pipelines, and platform governance.
Define platform roadmaps aligned with business objectives, technical constraints, and long-term scalability requirements.
Coordinate stakeholders across business and technical domains to ensure successful project execution and delivery.
Facilitate prioritization decisions, manage dependencies, and remove delivery blockers.
Monitor platform performance, adoption, operational efficiency, and continuous improvement opportunities.
Collaborate with architects and engineering teams to ensure platform solutions remain scalable, secure, and maintainable.
Promote best practices across cloud engineering, AI operations, infrastructure automation, and product development processes.