Product Manager

StratusGrid

2d•Remote

About The Position

StratusGrid is seeking a Product Manager to help shape Stratusphere, its AI-native platform for cloud infrastructure management. This hands-on role works at the intersection of customers, business, design, and technology. The Product Manager develops a deep understanding of users, buyers, markets, business needs, and the product, and partners closely with Product Design and Engineering to discover solutions that customers value, that are usable and technically feasible, and that work for the business. The role emphasizes product judgment, customer engagement, evidence-based discovery, and collaborative problem-solving rather than simply managing a roadmap or translating stakeholder requests into requirements. The Product Manager is expected to use AI extensively to accelerate research, analysis, prototyping, experimentation, and execution while retaining ownership of judgment and reasoning. They should be comfortable building prototypes and may use AI to contribute lightweight production code when useful. StratusGrid describes Stratusphere as a multi-agent platform that coordinates specialized infrastructure agents to observe AWS and Azure environments, simulate policy-safe plans, and execute approved changes with auditability and rollback-ready safety. The company focuses on trustworthy automation and measurable customer and business impact. The position requires periodic travel and the ability to work effectively on a distributed team. Applicants must be legally authorized to work in the United States; visa sponsorship is not offered.

Requirements

Experience managing B2B technology products, preferably SaaS, infrastructure, developer, cloud, AI, data, or another technically complex product.
Demonstrated experience solving customer and business problems with cross-functional teams rather than primarily managing feature requests, requirements, backlogs, or delivery schedules.
Ability to make high-quality decisions with incomplete information, identify important risks and assumptions, distinguish strong evidence from weak signals, and recognize when more discovery is needed.
Willingness and ability to spend meaningful time directly with customers and users, understand their work in context, and apply those insights to product decisions.
Understanding of how customer value, product strategy, pricing, go-to-market, enterprise buying behavior, operations, and company economics interact; ability to assess whether solutions work for both users and the business.
Experience building or managing products sold to organizations with multiple users, stakeholders, decision-makers, and buying or approval processes.
Ability to develop deep understanding of customers' technical environments, workflows, jobs-to-be-done, constraints, and problems; comfort speaking credibly with cloud, platform, infrastructure, FinOps, and engineering stakeholders.
Ability to reason about how cloud infrastructure, engineering workflows, organizational processes, and operational constraints shape customer behavior and product needs.
Ability to use product usage data, customer signals, experiments, operational metrics, and business data to identify problems, form hypotheses, evaluate opportunities, and measure outcomes.
Ability to collaborate with and influence Product Design, Engineering, Product Marketing, Sales, Customer Success, executives, and other stakeholders through context, evidence, judgment, and communication.
Strong written and verbal communication skills, including the ability to make complex product, technical, and business topics understandable to different audiences.
Ability to work effectively amid ambiguity and rapidly changing product, market, technology, and customer expectations.
Bias toward measuring success by customer and business results rather than roadmap completion, feature volume, or output.
Strong attention to detail, product taste, curiosity, and intellectual honesty; ability to move quickly while maintaining high standards of thinking.
Comfort using modern AI tools extensively for research, synthesis, analysis, ideation, prototyping, experimentation, and development, without substituting generated output for judgment, reasoning, or ownership.
Willingness and ability to travel periodically for customer engagements, team planning sessions, or onsite work.
Ability to work effectively on a distributed team, with reliable high-speed internet, a professional and distraction-limited workspace, and consistent independent communication, collaboration, and execution.
Legal authorization to work in the United States at the time of hire; visa sponsorship is not offered.

Nice To Haves

Direct familiarity with AWS, Azure, GCP, cloud economics, FinOps, infrastructure as code, platform engineering, observability, or adjacent technical domains.
Experience building products where AI agents, LLMs, automation, or machine learning are core parts of the product.
Familiarity with products involving autonomous or semi-autonomous agents, human-in-the-loop workflows, confidence systems, permissions, observability, evaluation, or automated execution.
Previous professional experience in software engineering, solutions engineering, data engineering, cloud engineering, or another hands-on technical discipline.
Experience in an early-stage or rapidly evolving company where product strategy, operating practices, and organizational boundaries were still being developed.
Experience discovering, validating, and bringing significant new products or capabilities from early concept through customer adoption.
Direct experience with technical products requiring security reviews, architecture reviews, procurement, change-management processes, or alignment across engineering and executive stakeholders.
Experience building products for engineers, platform teams, DevOps, SRE, FinOps, or other technical practitioners.
Experience using large or complex datasets, telemetry, analytics, or operational data as a core part of product discovery and decision-making.
Ability to identify confusing interactions, weak information architecture, unnecessary complexity, and opportunities to make sophisticated technical products simpler and more intuitive.
Hands-on experience using coding agents, AI IDEs, or other AI-assisted development environments to prototype, test, and ship working software.

Responsibilities

Work with product leadership, Design, and Engineering to translate company and product strategy into well-defined problems and measurable outcomes, and remain accountable for customer and business results.
Assess value and viability risks, including customer value, monetization, go-to-market, operational implications, legal and compliance constraints, and strategic fit.
Develop deep understanding of customers, users, prospects, their workflows and environments, and how they use Stratusphere by engaging directly with them and internal teams.
Partner with Product Design and Engineering in continuous discovery to explore problems, generate solutions, assess risks, prototype, experiment, and gather evidence before committing significant engineering effort.
Bring customer and business context to product development, collaborate on usability and experience with Design, and involve Engineering early for technical input.
Frame problems and opportunities using customer signals, business goals, product data, market context, and strategic priorities rather than starting with feature requests or predetermined solutions.
Use prototypes, AI-assisted development tools, data, simulations, and lightweight experiments to make ideas tangible and test assumptions; build prototypes when appropriate while respecting Design and Engineering ownership.
Combine qualitative customer learning with quantitative product and business data to understand behavior, diagnose problems, prioritize opportunities, evaluate solutions, and measure outcomes.
Develop knowledge of StratusGrid's business model, customers, pricing, go-to-market motion, competitive environment, partnerships, operational constraints, and strategic priorities, and apply it to product decisions.
Understand how enterprise technical products are evaluated, purchased, approved, deployed, and expanded, considering both technical users and business decision-makers.
Contribute customer, market, product, technology, and business insight to product strategy, identifying opportunities, tradeoffs, and market changes that should influence investment.
Prioritize opportunities based on impact and evidence, balancing risks, customer needs, strategic importance, and available capacity.
Define success measures, assess customer behavior and business impact after release, identify unexpected consequences, and iterate until intended outcomes are achieved or evidence supports a different direction.
Partner with Product Marketing on positioning, pricing and packaging inputs, launches, customer communication, and market learning.
Use modern AI tools to accelerate research synthesis, data analysis, competitive exploration, ideation, prototyping, experimentation, documentation, and execution, and develop repeatable workflows that improve product work.
Use AI and technical tools to work with systems, APIs, data, and code; build prototypes and occasionally contribute targeted production code when useful, respecting engineering standards and ownership.
Own work end to end across strategy, discovery, experimentation, delivery, measurement, and iteration; seek context, develop and communicate a point of view, make decisions, and close the loop.