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Senior Product Manager-Data – ML – And AI Products
| Company | Tekion |
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| Location | Pleasanton, CA, USA |
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| Salary | $163000 – $221700 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Senior |
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Requirements
- 4+ years of experience in AI-focused product management in B2B2C, B2B or B2C space
- Experience working in a SaaS offering in one or many of the following: Accounting, Payroll, CRM, ERP, DMS, eCommerce/Digital Retail, and Analytics.
- Proven track record of launching AI-driven enterprise SaaS solutions at scale.
- Deep understanding of LLMs, AI Agentic Platform, Generative AI and Predictive AI models
- Experience working closely and driving product requirements for Data Engineering, ML Engineering and Data Science teams.
- Ability to navigate and lead cross-functional teams through complex AI product development lifecycles.
Responsibilities
- Spearhead the development and implementation of cutting-edge AI solutions by crafting the vision, strategy, roadmap, and execution plan.
- Build detailed product requirements, narratives, and technical specifications driven by customer feedback and intuitive product thinking.
- Take the lead in re-imagining the end-to-end User Experience of our product, optimizing for an AI-first world across our Web and Mobile applications.
- Utilize data to deeply understand user needs and guide future product development. Build the necessary Analytics layer to enable data-driven decision making.
- Work closely with engineering, product design, cross-track product management and GTM teams to bring new capabilities to life.
- Stay ahead of the technology curve. Leverage Agentic AI, Generative AI, Predictive AI and Analytics to optimize dealership and enterprise workflows.
- Facilitate AI adoption within Tekion by assessing partnerships and driving POCs with innovative AI startups, data providers, and cloud vendors.
Preferred Qualifications
- Formal degree in a technical field such as Machine Learning, Statistics or Computer Science.
- Experience building product management teams at scale for growth.
- Familiarity with core AI platform stack such as Kubeflow, Pinecone, Langchain, etc.
- Knowledge of AI tooling stack across one/many Public Cloud and Data vendors: AWS Sagemaker, Azure ML, Google Vertex AI, Databricks, etc.
- Familiarity with LLM-based applications and AI-enhanced customer engagement tools.
- Strong technical acumen in cloud-based AI infrastructures and data pipelines.
- Experience in automotive, supply chain, or enterprise AI SaaS solutions.
- Experience managing large, technically complex engineering programs spanning multiple teams.
- A high degree of independent drive.
