Analysis of Customer and Market Signals Understands and starts to build experiences across multiple feature areas (e.g., product, service). Starts to coach internal team to develop problem statements and forms hypotheses of new feature areas (e.g., product, service) to address complex customer needs and/or market opportunities; identifies dependencies of other feature areas. Uses AI for trend analysis and sentiment evaluation to generate hypotheses, understand problems, and anticipate customer preferences, conducting experiments and A/B tests to improve model performance and inform feature development. Establishes clarity of patterns of root problem and how it relates with previously seen trends across customers, determines the customers/sectors impacted, foresees future opportunities, and provides research evidence to determine priorities. Collaborates with others (e.g., Software Engineering [SWE], Hardware Engineering [HWE], Product Marketing, Design, Security Subject Matter Experts) to ensure that they can satisfy customer and security requirements. Validates the market size and opportunity to determine products or features of greatest value. Defines and optimizes AI-driven solution options across multiple feature areas (e.g., product, service), incorporating insights into refinement and experimentation processes. Partners with senior colleagues on other teams (e.g., SWE, HWE) in refinement sessions to synthesize hypothesis results into solutions tied with Objectives and Key Results (OKRs) and Key Performance Indicators (KPIs) progress. Independently leverages AI to identify customers' unmet or unknown needs and market opportunities for enhancements or development of multiple feature areas (e.g., product, service) via quantitative (e.g., usage, telemetry) and qualitative analyses (e.g., customer usage, various listening systems, feedback channels of market and industry trends), looks for patterns in the data across a portfolio, analyzes security and ethical compliance, and scopes the impact and prioritization of a problem. Performs market or user research through AI in collaboration with the User Research team, conducts competitive analyses, and examines market and industry trends, as well as industry-specific requirements or regulations. Shares insights with internal team and ensures cross-team alignment on creating products that are easy to adopt and provide a positive experience for customers. Go To Market Evangelizes supported feature areas, including AI-driven solutions, with internal and external stakeholders, partners, analysts, and customers in the industry via presentations, blog posts, social media, and other forums. Presents at Executive Briefing Centers (EBCs) and large industry/company events. Acts as a primary interface with Product Marketing to educate on the product and leverages AI to develop content. Collaborates with Product Marketing, Business Planning, and Engineering to identify product release criteria (including security requirements such as Security Development Lifecycle (SDL) compliance), customer acquisition, usage, retention, and monetization strategies. May help scale Product Marketing teams by helping build marketing and roll-out plans and/or content such as product overviews, blogs, and landing pages for individual features or smaller products that ladder up to marketing plans for an overall product solution area. Creates and drives strategy for taking the multiple feature areas (e.g., product, service) from private preview to public preview and then to general availability. Contributes to creating and/or automating customer support plans (e.g., frequently asked questions [FAQs], scripts), HyperCase, change management, and communication plans. Product/Service Definition Identifies AI-informed, short-term, and long-term investment opportunities, evaluates tradeoffs, and prioritizes investments in consultation with cross-functional partners for multiple feature areas (e.g., product, service). Determines the features or experiences to prioritize in the roadmap that will support achievement of success criteria and Objectives and Key Results (OKRs). Works across multiple feature areas as directed. Helps write the product framing/vision memo, including AI-driven solutions, to address unmet or unknown customer needs and scope out opportunities across multiple feature areas. Helps distill the vision and strategy into a product roadmap, emphasizing AI as a core differentiator to address customer needs and market opportunities. Creates user stories and assists in building epics to convey the big picture. Leverages a deep understanding of the product architecture to design integrated scenarios. Utilizes AI to generate synthetic feedback to simulate user feedback and refine product vision memos, user stories, and scenarios, aiding in testing positioning, messaging, and feature value before launch. Integrates AI-first thinking into product strategy. Collaborates with others (e.g., Business Planning, Finance, Support, Customers, Product Marketing) to identify the potential customer base. Communicates product strategy to internal and external customers and builds consensus through multiple methods (e.g., conference presentations, collaboration with partner organizations. Drives, simulates, and tracks business impact across the organization and tracking success criteria and performance metrics (e.g., Objectives and Key Results [OKRs], Key Performance Indicators [KPIs] such as engagement, usage, acquisition, retention, user love/net promoter score (NPS), revenue, profitability, and in project features) and provides clarity on fundamentals (e.g., quality, privacy, security, compliance, accessibility, cost of goods sold [COGS]) of multiple feature areas. Independently sets and defines success metrics for AI related features and products (e.g., precision/recall, relevance scores). Works with internal partners (e.g., SWE and HWE) to identify needed data and ensure needed telemetry is developed, and obtains it responsibly and compliantly; reports and explicates reasons for outcomes. Deeply understands the COGS of multiple feature areas (e.g., product, service) and the KPIs that will help improve profitability. Identifies OKRs for multiple feature areas (e.g., product, service), and ensures alignment of the features with product-level OKRs, including success/performance metrics that represent the security posture of product or feature (e.g. percent of information being logged that is required for security investigations). Determines the value of the product or feature to business growth, aligns success criteria, and measures success. Translates technical AI concepts into business value, engaging with executives and customers to build consensus and support for AI-first product strategies. Influences and engages with cross-functional internal partners, external partners, including early adopting customers, senior leadership, and other key stakeholders to gather input and garner support for product/service vision, strategy, and roadmap for multiple feature areas. Starts to provide thought leadership for questions and challenges from group managers and other leaders. Anticipates push back and addresses it appropriately using product expertise and data while handling challenging feedback. Leverages AI-driven workflows to collaborate with cross-functional teams to gain buy-in and alignment. Solicits input from others regarding priorities and resources needed to deliver desired outcomes for multiple feature areas (e.g., product, service). Product/Service Development Collaborates with partner team to build golden configurations and drives scenario walkthroughs and thought exercises to identify problems, system friction, and needed contingencies in advance of early customer adoption for multiple feature areas (e.g., product, service). Shares feature previews or roadmap with customers to drive engagement and to gather feedback and customer telemetry in conjunction with others (e.g., Business Development, Sales, End Consumers, User Research). Collaborates with internal partners (e.g., SWE, HWE, and Scientists) to synthesize, prioritize, and address feedback to continuously refine AI-driven product strategies and roadmaps. Ensures that products or features related to security incorporate up-to-date Threat Model design into newest versions and that these products or features are reviewed by the internal Threat Model/Security teams. Leverages data and AI tools to analyze user behavior or feedback, working with data scientists or engineering to implement AI-driven improvements (e.g., training and fine-tuning models, rules). Owns the roadmap for the multiple feature areas (e.g., product, service) they own. Prioritizes the backlog, works with internal partners (e.g. SWE and HWE) to align on tradeoffs for the multiple feature areas (e.g., product service) they own, and partners with Product Marketing on the disclosure of the roadmap. Takes in new inputs and adapts as necessary. Starts to build AI-based systems and frameworks to enable the team to scale for a product area. Ensures line between customer needs and what is developed on the roadmap so that a series of problems can be addressed over time. Ensures alignment between the roadmap for the multiple feature areas (e.g., product, service) and Objective and Key Results (OKRs) and Key Performance Indicators (KPIs). Drives features that utilize AI and ensure they meet quality, security, privacy, and ethical standards. Defines the feature set and partners with Design teams to connect multiple design factors (e.g., visual design, user experience [UX], application programming interfaces [APIs], hardware design) to desired functionality and product vision. Develops user stories and scenarios that integrate AI outputs and align with user expectations and needs. Generates proof-of-concept designs through the use of Generative AI to explore wider design spaces. Independently builds minimally-viable-products (MVPs) and tests product concepts leveraging AI prototyping tools and auto-generated workflows. Collaborates with data science teams to establish model objectives, training data, and evaluation metrics, ensuring alignment with broader product goals. Iterates multiple designs with design partners in other teams (e.g. Design, SWE and HWE). Leverages preexisting design patterns and technical knowledge to inform current design iterations and establish a cohesive design approach. Anticipates interoperability challenges between different components or layers in the stack (e.g., UX and API layer differences). Facilitates mid-level reviews (e.g., UX, system designs, data designs) with customers (e.g., regulators, engineers, policy makers, business-decision makers) to determine usability and ensure accessibility criteria and updated designs meet customer goals. Incorporates security factors into design, such as logging posture (i.e. what needs to be logged for security investigations), permissions minimization (i.e. least level of permissions required to use product or feature), and having security enabled by default (i.e. resilient against prevalent threats and vulnerabilities without requiring additional configuration by the end user). Product/Service Performance Builds trust with a targeted selection of customers. Orchestrates and automates a line of communication with complex and advanced customers to capture feedback and insights through the product development lifecycle. Manages customer communities and customer engagement programs. Responds to real-time customer feedback in online portals, leveraging AI-driven workflows to improve efficiency. Understands and drives improvements in the support process, including both forums and communities. Utilizes customer personas as a framework and AI-based research to understand customers and communicate effectively. Partners with others (e.g., Data Science, SWE, HWE, User Research) to define and collect performance metrics (e.g., key performance indicators [KPIs] such as engagement, usage, acquisition, revenue, and in-project features), monitor model deployment and report on progress (e.g., business reviews), and derive deep insights and drives productive courses of action to improve product/feature development, iteration, AI integration, and implementation. Leverages customer listening systems, telemetry, engagements (e.g., interviews, surveys), etc., to develop insights on product performance and customer needs. Leverages technical knowledge on API, infrastructure, and/or AI modeling to form hypotheses to complex technical needs, performs experiments, iterates, and tests to drive improvement/adoption in specific performance metrics that have broad impact in a targeted area. Identifies features to deprecate based on AI-driven analytics. Develops, articulates, and presents reasoning and tradeoffs involved in deprecations. Works with Public Relations/Product Marketing on messaging to customers. Communicates change accurately. Identifies optimal next steps for customer transition. Bachelor's Degree AND 5+ years experience in product/service/program management or software development These requirements include but are not limited to the following specialized security screenings: Bachelor's Degree AND 8+ years experience in product/service/program management or software development OR equivalent experience. 2+ years experience taking a product, feature, or experience to market (e.g., design, addressing product market fit, and launch, internal tool/framework). 4+ years experience improving product metrics for a product, feature, or experience in a market (e.g., growing customer base, expanding customer usage, avoiding customer churn). 4+ years experience disrupting a market for a product, feature, or experience (e.g., competitive disruption, taking the place of an established competing product).
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