Product Operations Lead

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 .

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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.

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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.