Product Manager

OPPORTUNITY We're looking for a Product Manager to help shape the future of Stratusphere and work as part of an empowered product team solving meaningful customer and business problems. This is a hands-on product role at the intersection of customers, business, design, and technology. You'll develop a deep understanding of our users, buyers, market, business, and product, and work closely with Design and Engineering to discover solutions that customers value, are usable and technically feasible, and work for the business. We're building an AI-native platform for cloud infrastructure management in a market that is changing quickly. That means this role requires more than managing a roadmap or translating stakeholder requests into requirements. You'll be expected to develop strong product judgment, challenge assumptions, spend meaningful time with customers, use evidence to reduce risk, and work collaboratively with the team to discover the best solutions to important problems. You'll also be expected to use AI aggressively as a force multiplier, accelerating research, analysis, synthesis, exploration, prototyping, experimentation, and execution while maintaining personal ownership of the judgment, reasoning, creativity, and taste behind the work. You should be comfortable building prototypes yourself and, when it makes sense, using AI to contribute lightweight production code to help the team learn or move faster. RESPONSIBILITIES • Own Product Outcomes: Work with product leadership, Design, and Engineering to turn company and product strategy into clear problems to solve and measurable outcomes. Maintain focus on whether the work is creating meaningful customer and business results. • Own Value and Viability Risk: Develop the evidence and judgment needed to determine whether customers will choose to use or buy what we build and whether proposed solutions work for the business. Consider factors such as customer value, monetization, go-to-market, operational implications, legal or compliance constraints, and strategic fit. • Develop Deep Customer and User Understanding: Spend meaningful time with customers, users, prospects, Customer Success, Sales, and other stakeholders to understand workflows, pain points, motivations, behaviors, constraints, and unmet needs. Become an expert in how customers use Stratusphere and the environments in which they operate. • Drive Continuous Product Discovery: Work side-by-side with Product Design and Engineering to rapidly explore problems, identify opportunities, generate potential solutions, assess risk, build prototypes, run experiments, and gather evidence before committing significant engineering effort. • Partner Deeply with Design and Engineering: Treat product development as a collaborative problem-solving process rather than a handoff. Bring customer and business context, work with Design on experience and usability, and engage Engineering early enough for technical insight to shape the solution. • Frame Problems Before Solutions: Translate customer signals, business goals, product data, market context, and strategic priorities into well-framed problems and opportunities. Avoid treating feature requests or predetermined solutions as the starting point. • Prototype to Learn: Use prototypes, AI-assisted development tools, data, simulations, and lightweight experiments to quickly make ideas tangible and test assumptions. Build enough yourself when appropriate to accelerate learning without bypassing Design or Engineering ownership. • Use Data and Evidence to Make Decisions: Combine qualitative customer learning with quantitative product and business data to understand behavior, diagnose problems, prioritize opportunities, evaluate solutions, and measure whether shipped work is producing the intended outcome. • Understand the Business Deeply: Develop strong knowledge of StratusGrid's business model, customers, pricing, go-to-market motion, competitive environment, partnerships, operational constraints, and strategic priorities. Use that understanding to ensure product decisions create value for both customers and the company. • Understand Enterprise Buyers and Adoption: Develop a strong understanding of how technical products are evaluated, purchased, approved, deployed, and expanded within enterprise organizations. Account for the needs of both hands-on technical users and the leaders or economic buyers responsible for business outcomes. • Contribute to Product Strategy: Bring customer, market, product, technology, and business insight into product strategy. Identify emerging opportunities, important tradeoffs, and changes in the market that should influence where we invest. • Prioritize Based on Impact and Evidence: Make thoughtful tradeoffs across opportunities, risks, customer needs, strategic importance, and available capacity. Maintain focus on the highest-value problems rather than allowing urgency, stakeholder volume, or feature requests to dictate priorities. • Measure Outcomes After Release: Stay accountable after something ships. Define success measures, observe real customer behavior and business impact, identify unexpected consequences, and continue iterating until the intended outcome is achieved or the evidence indicates a different direction. • Work Closely with Product Marketing: Partner on positioning, pricing and packaging inputs, product launches, customer communication, and market learning. Bring deep product and customer context, contribute wherever your perspective or skills add value, and work collaboratively across functional boundaries when that helps the team move faster or produce a better outcome. • Create Leverage with AI: Use modern AI tools to accelerate customer-research synthesis, data analysis, competitive exploration, ideation, prototyping, experimentation, documentation, and execution. Build repeatable workflows that improve the speed and quality of product work without outsourcing judgment or critical thinking. • Contribute Technically When Useful: Be comfortable using AI to work with technical systems, APIs, data, code, and AI development tools. Build prototypes and occasionally contribute targeted production code when doing so is the fastest or most effective way to learn, unblock progress, or deliver value, while respecting engineering standards and ownership. • Own Your Work End to End: Move comfortably between strategy, discovery, experimentation, delivery, measurement, and iteration. Seek out the context you need, develop a point of view, communicate clearly, make decisions, and close the loop. REQUIREMENTS • Product Management Experience: Experience managing B2B technology products, preferably SaaS, infrastructure, developer, cloud, AI, data, or another technically complex product. • Empowered Product Mindset: Demonstrated experience solving customer and business problems with cross-functional teams rather than primarily managing feature requests, requirements, backlogs, or delivery schedules. • Strong Product Judgment: Ability to make high-quality decisions with incomplete information, identify the most important risks and assumptions, distinguish strong evidence from weak signals, and know when additional discovery is necessary. • Deep Customer Orientation: A willingness and ability to spend meaningful time directly with customers and users, understand their work in context, and use those insights to inform product decisions. • Strong Business and Commercial Judgment: An understanding of how customer value, product strategy, pricing, go-to-market, enterprise buying behavior, operations, and company economics interact. Ability to evaluate not only whether a solution can work for users but whether it works for the business. • Enterprise B2B Experience: Experience building or managing products sold into organizations with multiple users, stakeholders, decision-makers, and buying or approval processes. • Technical Domain Fluency: Ability to develop a deep understanding of Stratusphere customers' environments, workflows, jobs-to-be-done, constraints, and technical problems. Comfortable speaking credibly with cloud, platform, infrastructure, FinOps, and engineering stakeholders and asking the questions needed to uncover root causes, tradeoffs, and unmet needs. • Ability to Reason About Technical Use Cases: Able to understand how cloud infrastructure, engineering workflows, organizational processes, and operational constraints shape customer behavior and product needs. Translate that understanding into better problem framing, discovery, prioritization, and solution evaluation. • Strong Analytical Capability: Ability to work with product usage data, customer signals, experiments, operational metrics, and business data to identify problems, develop hypotheses, evaluate opportunities, and measure outcomes. • Cross-Functional Collaboration and Influence: Comfort working closely with Product Design, Engineering, Product Marketing, Sales, Customer Success, executives, and other stakeholders. Ability to create alignment through context, evidence, judgment, and communication. • Excellent Communication: Ability to make complex product, technical, and business topics understandable to different audiences. Strong written and verbal communication that helps teams reason clearly and make better decisions. • Comfort with Ambiguity: Ability to operate effectively when the product, market, technology, and customer expectations are changing quickly and many of the answers need to be discovered rather than inherited. • Outcome Orientation: A bias toward measuring success by customer and business results rather than roadmap completion, feature volume, or output. • High Standards for Craft and Judgment: Strong attention to detail, product taste, curiosity, and intellectual honesty. Ability to move quickly without lowering the bar for the quality of thinking. • AI Fluency: Comfort using modern AI tools extensively throughout the product management workflow, including research, synthesis, analysis, ideation, prototyping, experimentation, and development. Ability to use AI to increase leverage without substituting generated output for judgment, reasoning, or ownership. • Travel: Willingness and ability to travel periodically, as needed, for customer engagements, team planning sessions, or onsite work. • Remote-Work-Ready: Equipped to work effectively in a distributed team, including a reliable high-speed internet connection, a professional and distraction-limited workspace, and the ability to consistently communicate, collaborate, and execute independently. • Work Authorization: Applicants must be legally authorized to work in the United States at the time of hire. This position does not offer visa sponsorship. NICE-TO-HAVE / DIFFERENTIATORS • Cloud Infrastructure or FinOps Domain Experience: Direct familiarity with AWS, Azure, GCP, cloud economics, FinOps, infrastructure as code, platform engineering, observability, or adjacent technical domains. • AI-Native Product Experience: Experience building products where AI agents, LLMs, automation, or machine learning are core parts of the product rather than peripheral features. • Agentic-System Experience: Familiarity with designing or managing products involving autonomous or semi-autonomous agents, human-in-the-loop workflows, confidence systems, permissions, observability, evaluation, or automated execution. • Engineering Background: Previous professional experience in software engineering, solutions engineering, data engineering, cloud engineering, or another hands-on technical discipline. • Early-Stage Product Experience: Experience working in an early-stage or rapidly evolving company where product strategy, operating practices, and organizational boundaries were still being developed. • 0-To-1 Product Experience: Experience discovering, validating, and bringing significant new products or capabilities from early…