Product Development Operations Lead  at Samsung in Mountain View, CA

Product Development Operations Lead Location: 645 Clyde Avenue, Mountain View, CA, USA Position Summary We are seeking a Product Development Operations Lead — a strategic, cross-functional leader responsible for driving operational excellence across our Product and Engineering organization. This role sits at the nexus of strategic planning, process optimization, agile transformation, and data-driven governance, to enable high-velocity delivery of high-quality products in a dynamic ad-tech landscape. You will own the operating cadence of our product development lifecycle — from portfolio planning and roadmap execution to metrics-driven performance governance. You will champion automation and Generative AI as force multipliers for operational efficiency, and you will be the connective tissue that ensures our teams plan better, execute faster, and learn continuously. This is not a traditional project management role. This is a systems thinker and operational strategist role for someone who thrives on designing the machinery that makes great product development organizations run. Role and Responsibilities KEY RESPONSIBILITIES 1. Operating Cadence & Portfolio Planning Design, implement, and own the end-to-end operating cadence for the product and engineering organization — including annual planning cycles, roadmap reviews, and executive stakeholder readouts. Drive portfolio-level planning processes that align product strategy with business objectives, resource capacity, and technical dependencies. Establish and manage intake, prioritization, and trade-off frameworks to ensure the highest-impact work is funded and sequenced. Facilitate cross-functional and cross-site roadmap alignment across Product, Engineering, Design, and Business stakeholders. 2. Process Optimization & Automation Identify, design, and implement process improvements across the product development lifecycle — from ideation through release and post-launch review. Champion automation-first thinking — eliminate manual, repetitive operational overhead through workflow automation, scripting, and intelligent tooling. Leverage Generative AI (GenAI) capabilities to accelerate operational processes including (but not limited to): Automated status reporting and stakeholder communications AI-assisted sprint/release documentation Predictive analytics for delivery risk and capacity forecasting Build and maintain playbooks, templates, and standardized workflows that create consistency without stifling team autonomy. 3. Agile Transformation & Delivery Excellence Lead and evolve agile practices (scrum, SAFe etc.) across multiple product and engineering teams to optimize for speed, quality, and predictability. Partner with Engineering Leadership to drive continuous improvement in delivery velocity, cycle time, lead time, and flow efficiency. Build Agile Community of practice that serves as a grassroots engine for learning, alignment, and continuous improvement around Agile practices. 4. Tooling & Technology for Operational Excellence Manage the operational tech stack, ensuring consistent tooling adoption (e.g., Jira, Confluence) and maintaining data accuracy and governance. Own the product development toolchain strategy — evaluate, implement, and optimize tools for portfolio management, collaboration, documentation, and reporting. Stay current on emerging AI/ML-powered DevOps and product ops tooling and bring forward recommendations for adoption. 5. Analytics, Metrics & Governance Define and maintain a product development metrics — including KPIs for delivery performance (velocity, throughput, cycle time, defect rates), planning accuracy, and operational health. Build and own executive-grade dashboards and reporting that provide real-time, data-driven visibility into roadmap execution, resource utilization, and risk. Establish governance mechanisms — review cadences, escalation paths — that ensure accountability. Report regularly to senior leadership on portfolio health, delivery performance, and operational maturity with actionable insights and recommendations. 6. Cross-Functional Leadership & Change Management Serve as the operational connective tissue between Product, Engineering, Design, Data, QA, and Business stakeholders. Lead change management for new processes, tools, and ways of working — driving adoption through influence, communication, and demonstrated value. Build and foster a culture of operational discipline, transparency, and continuous improvement. [If applicable] Build, lead, and develop a team of Program Managers, Delivery Managers, or Product Operations Analysts. Required Core: 10+ years of experience in product operations, program management, technical program management, agile delivery. 3+ years in a leadership or senior individual contributor role driving operational excellence across multiple product/engineering teams Deep expertise in Agile/Lean methodologies (Scrum, Kanban, SAFe, Lean Portfolio Management) with hands-on experience in agile transformation. Demonstrated experience designing and implementing planning cadences, portfolio management processes, and governance frameworks at scale. Proven track record of leveraging automation, tooling, and data analytics to drive operational efficiency and eliminate waste. Hands-on experience with product/project management tools (Jira and Confluence) including advanced configuration, reporting, and integrations. Strong analytical and quantitative skills — comfortable building metrics frameworks, dashboards, and deriving insights from delivery data. Excellent communication and facilitation skills — ability to operate effectively from the team level to the C-suite. Experience working in fast-paced, high-growth environments with rapidly evolving priorities. Technical: Experience building automated reporting pipelines — pulling data from multiple sources (Jira, Git, CI/CD, spreadsheets) into unified dashboards and stakeholder-ready outputs. Working knowledge of scripting languages (Python, JavaScript, or similar) for building custom automation scripts, data extraction, and API integrations. Demonstrated, hands-on experience applying Generative AI tools and techniques to real-world operational and business workflows — not just conceptual familiarity. Awareness of responsible AI practices — including data privacy, bias mitigation, hallucination management, and governance considerations when deploying GenAI in enterprise workflows. Ability to evaluate, pilot, and scale emerging GenAI tools and capabilities — acting as the organization's operational AI champion. Skills and Qualifications Preferred Experience in the ad-tech, or digital media industry. Working knowledge of or hands-on experience applying Generative AI tools (e.g., Claude, ChatGPT, GitHub Copilot, custom LLM integrations) to operational workflows. Experience building or implementing AI/ML-powered automation for reporting, forecasting, or workflow optimization. Familiarity with data engineering and data product development lifecycles. Background in or strong understanding of software engineering practices, CI/CD, and DevOps principles. Experience with BI/analytics tools (EasyBI, Looker, Power BI, or similar) for building operational dashboards. Certified SAFe Program Consultant (SPC), PMI-ACP, CSM/CSP, or equivalent certifications. 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