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Vertex is a global biotechnology company that invests in scientific innovation.
Principal Product Manager – AI Solutions
Location
United States
Posted
79 days ago
Salary
$189.6K - $246.4K / year
Seniority
Lead
No structured requirement data.
Job Description
Principal Product Manager – AI Solutions
Vertex Inc.
Role Description This Principal Product Manager – AI Solutions role is a hands-on, individual contributor position that creates and delivers AI-first product capabilities for Vertex customers by translating ambiguous problems into clear hypotheses, product requirements, and roadmap priorities. The role partners closely with tax domain subject matter experts (SMEs), engineering, UX, go-to-market, and customer success to ship production-ready AI that is trusted and compliant, integrates into workflows, and demonstrates value through evaluation, monitoring, and performance metrics. This role is not a tax SME; it is an innovation and product leadership role that identifies opportunities, prototypes solutions, and scales what works. Qualifications - Minimum of six (6) years of relevant product management experience. - Principal-level success includes owning multi-quarter roadmaps, aligning cross-org stakeholders, and leading complex, cross-functional initiatives from ambiguous problem definition through 0→1 discovery, launch, rapid iteration, and scaled releases with measurable customer and business outcomes. - 2+ years of direct AI experience (e.g., system design and/or development). - Experience defining AI product requirements beyond feature scope, encompassing data strategy, learning signals, feedback loops, and measurable success criteria. - Strong command of AI product quality and reliability, including how drift, regressions, and performance tradeoffs affect user trust and adoption. - Excellent product leadership fundamentals, including systems-level thinking, executive communication, and the ability to lead through influence in complex, matrixed organizations. - Set and own standards for AI product effectiveness, including success metrics, monitoring, and continuous improvement across quality, reliability, usage, cost, and performance. - AI fluency (required): able to prototype, evaluate, and operationalize AI-first capabilities in partnership with engineering and SMEs. - Define features and capabilities by creating lightweight prototypes; translate AI capabilities and constraints into clear product requirements. - Lead evaluation, tuning, and training in partnership with engineering and SMEs, including defining evaluation criteria and interpreting results. - Refine requirements, UX behaviors, acceptance criteria, and release readiness decisions by connecting evolving AI capabilities to customer problems. - Apply responsible AI principles (traceability, privacy, security, bias awareness, transparency, auditability) within owned features and capabilities. - Maintain working fluency in modern AI/ML concepts (LLM-based solutions, agents, data pipelines) and use that fluency to experiment directly for faster product discovery and prototyping. Requirements - Bachelor’s degree in engineering, business, or a related field, or equivalent combination of education, training, and relevant professional experience. - Experience identifying cross-product innovation opportunities and driving roadmap alignment through APIs, integrations, and shared platform capabilities. - Experience mentoring or coaching junior product owners on AI fluency and product development practices. Other Qualifications - Communicate with Clarity: Be clear, concise and actionable. Be relentlessly constructive. Seek and provide meaningful feedback. - Act with Urgency: Adopt an agile mentality - frequent iterations, improved speed, resilience. 80/20 rule – better is the enemy of done. Don’t spend hours when minutes are enough. - Work with Purpose: Exhibit a “We Can” mindset. Results outweigh effort. Everyone understands how their role contributes. Set aside personal objectives for team results. - Drive to Decision: Cut the swirl with defined deadlines and decision points. Be clear on individual accountability and decision authority. Guided by a commitment to and accountability for customer outcomes. - Own the Outcome: Defined milestones, commitments and intended results. Assess your work in context, if you’re unsure, ask. Demonstrate unwavering support for decisions. Pay Transparency Statement US Base Salary Range: $189,600.00 - $246,400.00. Base pay offered to new hires may vary based upon factors including relevant industry and job-related skills and experience, geographic location, and business needs. The range displayed does not encompass the full potential of the role, which allows for further growth and career progression. In addition, as a part of our total compensation package, this role may be eligible for the Vertex Bonus Plan (VOB), a role-specific sales commission/bonus, and/or equity grants.
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Role Description Responsável pela gestão do backlog, definição de prioridades e acompanhamento da entrega, garantindo alinhamento entre negócio e tecnologia. - Criar e gerenciar backlog (user stories) - Priorizar demandas com base em valor de negócio - Acompanhar entregas junto ao time de desenvolvimento - Interagir com stakeholders - Garantir clareza de escopo e objetivos Qualifications - Pelo menos 5 anos de experiência como Product Owner - Vivência com metodologias ágeis (Scrum/Kanban) - Capacidade de traduzir negócio em requisitos - Experiência com gestão de backlog - Proficiência em uso de IA para suas atividades Requirements - Experiência com produtos digitais complexos - Conhecimento em métricas de produto - Vivência com times de tecnologia e IA Benefits - Oportunidades 100% remotas 👨🏻💻 - Vale home office 💻 - Feedbacks periódicos 💬 - Programa de indicações 🏅 - Acolhimento psicológico 🙋🏻♂️ - Ginástica laboral 🏋️ - Academia de conhecimento 🧠 - Convênio com escola de inglês 🔤 - Reuniões mensais de transparência 🔃 - Happy hour online 🍻 - Kit de boas-vindas 🎁
• Leadership in Discovery: Lead ongoing product discovery processes to identify users' latent pains, using qualitative and quantitative methods to validate hypotheses before development. • Roadmap Vision: Define and maintain the tribe's medium- and long-term product strategy, ensuring alignment with the company's OKRs. • Strategic Prioritization: Use frameworks to manage the backlog, balancing innovation, technical debt, and the needs of stakeholders and customers. • Communication: Serve as the link between the business, engineering, and other areas, translating technical complexities into clear requirements and communicating assertively. • Value Management: Ensure backlog items reflect strategic decisions and deliver value. • Product Refinement: Break down Epics and User Stories focused on outcomes, defining strict acceptance criteria that guarantee delivery quality. • Collaboration with Engineering: Support the development team across all cadences, removing impediments and ensuring smooth workflow. • Validation and Sign-off: Functionally validate deliverables, ensuring the end-user experience matches what was validated during Discovery. • Results Analysis: Monitor the performance of launched features using data, iterating the product based on real behavior and success metrics.
• Own the "what" and "why" behind product building • Define problems worth solving and set priorities • Ensure features ship with clear success metrics • Collaborate across engineering, design, and stakeholders • Align teams around shared plans without relying on authority
Staff Product Manager
vCluster LabsvCluster Labs is a venture-backed tech startup headquartered in San Francisco, California, with a distributed, remote-first team spanning eight time zones. Foun
• Technical Roadmap Ownership: Set the roadmap for your product surface and translate strategy into specs engineering can execute against. We'll align scope to your background — a hyperscaler KaaS PM might own the vCluster platform, a bare metal or GPU cloud PM might own vMetal, a multi-tenancy specialist might own platform + vNode. • Founder Partnership: Work directly with the Head of Product and Engineering leadership on the architecture tradeoffs that determine the product's trajectory. • Hands-on Validation: Run alpha and beta builds yourself. Catch integration issues before customers do. • Customer Intelligence: Engage directly with platform engineers at AI Cloud operators, regulated enterprises, and large internal platform teams. The next zero-to-one comes from these conversations. • Market Positioning: Track the cloud-native ecosystem and emerging tenancy primitives. Sharpen the narrative for technical buyers and partner with GTM on messaging that lands. • Cross-Functional Leadership: Bridge engineering, sales, and marketing so what we ship matches how we sell and support it.

