Description
We are seeking a visionary AI Product Lead to spearhead our Generative AI solutions portfolio. This pivotal role involves defining the product vision, strategy, and roadmap for our enterprise-ready AI applications. You will be the crucial link between executive strategy and technical execution, translating complex business needs into actionable requirements for our engineering and data science teams. The ideal candidate will guide the entire product lifecycle, from ideation to launch and iteration, for innovative tools like intelligent assistants and automated content generators. You will collaborate closely with UX designers, compliance experts, and sales to deliver commercially successful products. A key responsibility will be to navigate the rapidly evolving AI landscape, evaluating new models and vendor partnerships to maintain our competitive edge. Ultimately, you will champion the development of powerful, ethical, and compliant AI solutions that drive significant business value for our clients.
Requirements
1. 5–8 years of product management experience in a technology-driven environment.
2. A minimum of 3 years of direct experience in launching and managing AI/ML products, with a strong focus on Generative AI.
3. Demonstrated expertise with large language models (LLMs), foundational models, and their respective APIs (e.g., OpenAI, Anthropic, Google Gemini, open-source models).
4. Proven track record of integrating complex AI solutions into enterprise-level systems and workflows.
5. Experience defining product requirements and user stories for data science or machine learning engineering teams.
6. Deep understanding of the MLOps lifecycle, including data pipelines, model training, and performance monitoring.
7. Strong knowledge of ethical AI principles, data privacy regulations (e.g., GDPR), and AI governance frameworks.
8. Excellent stakeholder management skills with proven ability to communicate complex technical concepts to non-technical audiences.
Desirable
1. Advanced degree (MS or PhD) in Computer Science, AI, Data Science, or a related quantitative field.
2. Experience with Retrieval-Augmented Generation (RAG) and fine-tuning techniques for LLMs.
3. Familiarity with major cloud platforms (AWS, GCP, Azure) and their AI/ML service offerings.
4. Experience in B2B SaaS product management.
5. Prior experience in a specific industry vertical such as finance, healthcare, or logistics.