Technical Product Manager
1 week ago
Overview:
We're seeking a Product Owner with strong experience in data and AI projects, who can drive the delivery of innovative, data-driven solutions. In this role, you will act as the bridge between business stakeholders and technical teams, ensuring that AI and data initiatives are aligned with strategic goals. You should have hands-on experience with Microsoft Azure and Databricks, with a deep understanding of AI workflows, machine learning pipelines, and data platforms. This is a high-impact role, focused on leveraging AI to solve real business problems and create measurable value.
Key Responsibilities:
- Define, maintain, and prioritize the product roadmap for AI and data initiatives, ensuring alignment with organizational strategy.
- Collaborate with data engineers, data scientists, ML engineers, and business stakeholders to gather requirements, define KPIs, and prioritize features.
- Translate complex business problems into actionable user stories, AI workflows, and technical requirements.
- Partner with teams operating in Azure and Databricks to support the end-to-end lifecycle of data pipelines, analytics solutions, and machine learning models.
- Ensure that AI models and data solutions meet quality, performance, and business expectations, monitoring project progress and identifying risks.
- Serve as the voice of the customer, championing data-driven solutions and ensuring that product features deliver tangible business value.
- Drive alignment across teams to ensure AI initiatives are deployed efficiently and effectively, from experimentation to production.
- Stay abreast of the latest AI trends, tools, and frameworks, ensuring the organization leverages modern approaches to machine learning, generative AI, and advanced analytics.
Requirements:
- Proven experience as a Product Owner, Technical Product Manager, or similar role leading AI/data projects.
- Hands-on experience with Microsoft Azure services (Data Factory, Synapse, Machine Learning, Cognitive Services, etc.) and Databricks for AI and data analytics workloads.
- Strong understanding of data modeling, analytics, feature engineering, machine learning workflows, and AI deployment pipelines.
- Experience translating complex AI/ML concepts into business terms for non-technical stakeholders.
- Familiarity with Agile/Scrum methodologies and experience working in iterative product development cycles.
- Ability to balance strategic vision and tactical execution, ensuring projects are delivered on time while meeting high-quality standards.
- Passion for leveraging AI to solve real-world business problems, and a continuous learner of emerging AI technologies.
Preferred:
- Experience with generative AI models, natural language processing (NLP), or large-scale ML deployments.
- Knowledge of MLOps practices, including CI/CD for ML pipelines and model versioning.
- Familiarity with data governance, ethical AI practices, and explainable AI frameworks.
- Previous experience in enterprise AI initiatives impacting multiple business units.
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