Interim Technical PO- AI & Data Platform Engineering

Role OverviewThe AI & Data Platform Product Manager defines what gets built. As the Technical Product Owner, you are responsible for how it is delivered.

Delivery & Planning

• Break down epics into actionable tickets with clear acceptance criteria, dependencies, and Definition of Done
• Define delivery approaches, sequencing, and implementation strategies together with Engineering Leads
• Own effort estimation, capacity planning, and delivery forecasting
• Plan release readiness, deployments, environments, security reviews, access management, and monitoring

Team Leadership

• Manage day-to-day delivery operations of the engineering team
• Ensure transparency and quality across planning and execution
• Track progress based on engineering evidence (PRs, deployments, pipeline runs, releases, IaC changes)
• Identify blockers, delivery risks, capacity constraints, and scope creep early
• Balance platform development with enablement and support of product teams

Technical Oversight

• Participate in architecture and design reviews
• Manage cross-workstream dependencies across platform components and connected systems
• Make technical risks visible, including technical debt, security findings, reliability, performance, data quality, and cost

Portfolio & Stakeholder Management

• Own quarterly planning, roadmap preparation, and portfolio reporting
• Maintain a consolidated view of active and planned initiatives
• Translate technical complexity into clear decision options for leadership
• Identify capability and resource gaps and support resource planning

Stakeholder & Delivery Interface

• Act as the primary interface between the CoE and the delivery organization
• Assess technical feasibility and effort for new initiatives
• Coordinate and govern Proofs of Concept (PoCs), including scope, success criteria, effort, and decision points

Anforderungsprofil

Required ExperienceHands-on Technical Background

• Several years of practical experience as a Data, AI/ML, Platform, Cloud, or Software Engineer before moving into a product or delivery role
• Strong understanding of AI/ML lifecycles, MLOps, and LLMOps
• Experience with GenAI/LLM platforms, Agentic AI, RAG, embeddings, vector databases, and model serving
• Knowledge of Context Engineering and Semantic Memory concepts
• Data engineering experience, including batch and streaming architectures (e.g., Apache Spark)
• Strong Databricks expertise (Delta Lake, Unity Catalog, MLflow)
• AWS experience (IAM, networking, storage)
• Infrastructure as Code (Terraform or similar)
• CI/CD pipelines and Git-based development workflows
• Security best practices for AI, cloud, and data platforms
• Ability to review code, pull requests, pipelines, and architecture artifacts to assess delivery progress and risk

Delivery & Product Leadership

• Proven experience as a Technical Product Owner, Technical Program Manager, or Technical Delivery Lead
• Strong SDLC knowledge and experience with Agile methodologies (Scrum/Kanban) and Jira
• Expertise in estimation, capacity planning, roadmap planning, and portfolio management
• Strong stakeholder management skills, including communication with senior leadership
• High credibility with engineering teams and the ability to drive accountability