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 itura. . 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 effectivenessura. . Identify and implement process improvements to enhance speed and efficiencyura. . Leverage data insights to drive continuous optimization of product operations workflowsura. . Own and optimize tooling and dashboards to provide real-time visibility into product healthura. . 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 companyura. . Experience with feature or Product delivery, value driven decision making and coordinating product launches and releasesura. . Experience in agile & kanban development, release processes,and change managementura. . Hands-on daily use of AI tools in real work,with concrete examples of what changed as a resultura. . Proficiency in JIRA, Confluence, or similar release tracking toolsura. . Data-driven mindset with experience in tracking and analyzing product performance metrics, overseeing execution strategy and tactical improvementsura . Comfortable contributing to engineering discussions around technology decisions and strategy related to a product pipelineura . Excellent communication, collaboration,and stakeholder management skills.
Desired Skills
- Knowledge of SaaS business models, pricing strategies,and GTM executionura. . Familiarity with customer adoption and retention analyticsura. . Experience working with API-first or developer-focused productsura. . Experience building internal tools or automations that other teams actually adoptedura. . Familiarity with LLM-based workflows — prompt and agent design, MCP connectors, or similar.
Success Metrics
- Efficient and predictable releases,with minimal delays or incidentsura. . Stronger cross-functional coordination, improving launch readinessura. . Standardized product operations processes, improving efficiency and scalabilityura. . Data-driven decision-making, leveraging insights to optimize release and launch performanceura. . Higher product adoption rates, increasing user engagement and retentionura. . Reduced manual operational load,with recurring coordination and reporting work replaced by AI-assisted workflows and internal tooling.
