Product Operations Lead

About the Role

About the Role We are seeking a Product Operations Lead to play a key role in product launches, planning processes, AI adoption and operational efficiency. This role will ensure product availability, process optimization, and KPI tracking, working cross-functionally with Product, Engineering, Marketing, and Customer Success teams. The ideal candidate will drive seamless product delivery, scale best practices, and enhance the product management lifecycle. Key Responsibilities Product Launch & Go-to-Market Readiness • Drive cross-functional product launch planning, ensuring clear responsibilities and execution timelines. • Develop together with Product Marketing scalable launch playbooks to standardize and optimize the GTM process. • Track and measure launch success through key metrics such as adoption, usage, and retention. • Ensure internal teams are enabled with product documentation, updates, release notes and other enablement principles • Partner with Customer Success to optimize post-launch support and user experience. • Monitor product readiness and ensure alignment between Product, R&D, Support and GTM teams. AI & Builder Approach • Work AI-first - use Claude and the connected stack (JIRA, Confluence, Vitally, Gong, Slack) as the default method for drafting, analysis, and synthesis, not an occasional shortcut. • Build the tooling you need. Ship lightweight internal tools - scripts, agents, digests, dashboards - that remove recurring manual work in release and launch operations, without waiting for an engineering roadmap slot. • Contribute to Product Brain, our internal AI knowledge layer, and design operational workflows that pull context from connected systems rather than reassembling it by hand each cycle. • Own AI adoption within Product Operations - find the manual work a system should be doing, prototype the replacement, and prove it works before asking anyone to adopt it. • Apply judgment on where automation belongs. Know which decisions, escalations, and communications need a human, and keep those human. KPI Tracking & Operational Excellence • Define and track key performance indicators (KPIs) to measure release and launch effectiveness. • Identify and implement process improvements to enhance speed and efficiency. • Leverage data insights to drive continuous optimization of product operations workflows. • Own and optimize tooling and dashboards to provide real-time visibility into product health. • Partner with R&D to streamline deployment workflows, product maintenance and incident response guidelines. Qualifications & Experience Required Skills & Experience • At least 7 years in Product Operations, Business Development or Product Lifecycle Management within a SaaS or technology-driven company. • Experience with feature or Product delivery, value driven decision making and coordinating product launches and releases. • Experience in agile & kanban development, release processes, and change management. • Hands-on daily use of AI tools in real work, with concrete examples of what changed as a result. • Proficiency in JIRA, Confluence, or similar release tracking tools. • Data-driven mindset with experience in tracking and analyzing product performance metrics, overseeing execution strategy and tactical improvements • Comfortable contributing to engineering discussions around technology decisions and strategy related to a product pipeline • Excellent communication, collaboration, and stakeholder management skills. Desired Skills • Knowledge of SaaS business models, pricing strategies, and GTM execution. • Familiarity with customer adoption and retention analytics. • Experience working with API-first or developer-focused products. • Experience building internal tools or automations that other teams actually adopted. • Familiarity with LLM-based workflows — prompt and agent design, MCP connectors, or similar. Success Metrics • Efficient and predictable releases, with minimal delays or incidents. • Stronger cross-functional coordination, improving launch readiness. • Standardized product operations processes, improving efficiency and scalability. • Data-driven decision-making, leveraging insights to optimize release and launch performance. • Higher product adoption rates, increasing user engagement and retention. • Reduced manual operational load, with recurring coordination and reporting work replaced by AI-assisted workflows and internal tooling.