Product Manager-AI Prompt Engineering
2 days ago
Join us on a transformative journey as we enhance our operating model to drive productivity and innovation. We started by adopting Scrum in 2017 to boost team-level efficiency, then introduced a Product Operation Model to improve collaboration and alignment across products (team-of-teams). We've organized our products into Portfolios to optimize resource management and prioritization. Our current focus is on accelerating the delivery of our most significant priorities, which span multiple portfolios and many autonomous products.
As a Product Manager in the Product Operations team, you will focus on prompt engineering at scale, designing and deploying production-ready prompts that deliver real business value for the Product Operations function. You will translate complex business needs into AI-promoten prompt solutions that improve efficiency, automate processes, and generate actionable insights. On occasions when a solution requires development beyond prompt engineering, you will step into a Product Manager capacity – drafting requirements, coordinating with engineering teams, and ensuring successful execution.
Job responsibilities
- Design and deploy production grade prompts to address business challenges ranging from data synthesis and reporting to workflow automation and process optimization.
- Collaborate with business stakeholder to understand requirements and convert them into prompt-based AI solutions.
- Act as a Product Manager (in limited cases) for AI/ML initiatives requiring additional engineering work. Write requirements, manage dependencies, and coordinate delivery.
- Engage with cross functional teams (engineering, training, change management) to ensure prompt and AI/ML solutions are integrated smoothly and responsibly.
- Maintain a backlog of prompt engineering use cases, prioritize based on business value and deliver iteratively in alignment with product operations function goals.
- Enable teams to effectively use developed prompt/AI ML solutions through documentation, trainings and knowledge sharing.
Required qualifications, capabilities, and skills.
- 10+ years of work experience, with exposure to product management, engineering, or data/AI driven roles. (Not all years need to be in AI/ML, what matters is depth in problem solving and delivery at scale.
- Hands-on expertise with large language models (LLMs) and proven experience in creating effective, production- ready prompts and AI solutions.
- Working knowledge of AI/ML concepts and how they apply to real-world business problems.
- Good understanding of PDLC and SDLC, with practical experience applying Agile methodologies in large, complex organizations.
- Excellent stakeholder management skills, able to translate between technical and non-technical audiences.
- Strategic problem-solving ability with an execution- first mindset- comfortable moving from whiteboard to working solution quickly.
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