Technical Lead- AI Stack, Staff Engineer

Job description

**Job Area:** Engineering Group, Engineering Group > Software Engineering **General Summary:** **Role Summary** We are looking for a Technical Program Lead with strong Agile and Scrum delivery experience to drive large-scale, cross-functional development across the Data Center AI software stack. You will establish and run an effective execution cadence, enable teams to deliver predictably, and ensure transparent, data-driven decision-making. This role partners closely with Engineering, Product, and partner teams to manage scope, dependencies, risks, and releases across multiple teams, sites, and geographies. **Key Responsibilities** - Lead end-to-end program execution across multiple Agile teams delivering components of the AI software stack (models, frameworks, compilers, runtimes, serving, and platform interfaces). - Own and maintain the integrated plan (Plan of Record), aligning roadmaps to milestones, dependencies, capacity, risks, and delivery commitments. - Partner with Product and Engineering to translate strategy into an executable backlog and release plan; facilitate prioritization and trade-off decisions. - Establish and run Agile operating cadences (sprint planning, daily standups, reviews, retrospectives), and drive cross-team alignment via Scrum-of-Scrums / program syncs. - Coordinate execution across distributed teams and geographies, ensuring clear ownership, dependency management, and shared definitions of done/ready. - Drive release planning and change management (scope control, readiness criteria, go/no-go), ensuring predictable delivery and stakeholder visibility. - Proactively identify and remove impediments; track and mitigate delivery, technical, schedule, and integration risks with owners and due dates. - Communicate clearly with stakeholders at all levels; facilitate decision-making and alignment without direct authority. - Create transparent program reporting with Agile metrics (velocity trends, burn-up/down, cycle time, throughput, quality signals) and delivery confidence. - Drive continuous improvement across teams by coaching Agile practices, improving flow efficiency, and strengthening cross-team collaboration and release readiness. **Minimum Qualifications** - 8+ years of experience in program/project management delivering software in Agile environments (Scrum/Kanban), including multi-team initiatives. - Working knowledge of modern AI/ML software systems and the ability to collaborate effectively with engineering teams on technical dependencies and trade-offs. - Demonstrated ability to plan and deliver cross-functional programs involving Product, Engineering, QA, Operations, and partner teams. - Experience working with distributed teams and managing execution across time zones and stakeholder groups. - Strong facilitation and communication skills, with a track record of influencing outcomes without direct authority. - Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience). **Preferred Qualifications** - Scrum Master / Agile certification (CSM/PSM, SAFe, PMI-ACP) and experience applying Agile at scale (multi-team planning and dependency management). - Proficiency with Agile tooling and reporting (e.g., Jira, Azure DevOps) and building lightweight dashboards for stakeholders. - Experience driving release readiness and quality practices (definition of done, acceptance criteria, test planning, defect triage) for complex software systems. - Technical familiarity with AI/ML platforms or cloud-native delivery (containers, orchestration, CI/CD, MLOps) to effectively manage dependencies and risks. - Experience partnering with senior leadership on roadmap reviews, planning cycles, and executive-ready status communication. **Core Competencies** - Servant leadership mindset with strong facilitation across Scrum ceremonies and cross-team forums. - Execution excellence: ability to drive predictable delivery using Agile planning, clear working agreements, and data-driven inspection/adaptation. - Strong stakeholder and dependency management across Product, Engineering, and partner teams; comfortable operating in ambiguity. - Clear, structured, executive-ready communication with concise narratives, risks, and asks. - Ownership and accountability for outcomes, with a continuous-improvement approach to process and team health. **What Success Looks Like** - Predictable delivery of committed milestones and releases, with stable velocity/throughput trends and transparent scope management. - Reduced cross-team friction through effective dependency management, clear interfaces, and proactive risk/impediment removal. - Improved execution visibility via simple, trusted reporting and actionable Agile metrics (burn-up/down, cycle time, quality) that drive timely decisions. - Strong stakeholder trust built through reliable commitments, effective facilitation, and continuous improvement in team delivery and quality.