Note: The job is a remote job and is open to candidates in USA. NielsenIQ is the world’s leading consumer intelligence company, delivering comprehensive insights into consumer behavior. They are seeking a Senior Director of Engineering to lead the transformation of customer-facing SaaS product engineering capabilities towards an AI-first model, ensuring high-impact product outcomes and engineering excellence.
Responsibilities
- Lead the evolution of customer-facing SaaS product engineering capabilities from a mature SaaS model toward an AI-first product and engineering model
- Drive AI-enabled product innovation that improves customer workflows, decision support, automation, insight generation, and product differentiation
- Apply practical understanding of GenAI tools and AI-assisted engineering practices to improve SDLC effectiveness, developer productivity, software quality, testing, documentation, and modernization efforts
- Partner with product, architecture, security, privacy, data governance, and responsible AI stakeholders so AI-enabled capabilities are implemented thoughtfully within enterprise standards
- Define and communicate technical direction for customer-facing SaaS product engineering capabilities in alignment with product strategy, business priorities, and long-term platform evolution
- Provide deep technical leadership in architecture reviews, system design discussions, and critical engineering tradeoff decisions
- Guide the design and modernization of large-scale distributed systems, cloud-native services, APIs, data-intensive product platforms, and integrated user experiences
- Challenge existing technical approaches and identify opportunities to improve scalability, reliability, performance, security, maintainability, cost efficiency, and customer value
- Raise the engineering bar around system design, design discipline, architectural decision-making, and long-term technical sustainability
- Drive engineering delivery outcomes across complex, customer-facing SaaS product capabilities while ensuring alignment across Product, Architecture, Engineering, and Business stakeholders
- Translate product and business goals into executable engineering direction, prioritization, and delivery plans through senior engineering leaders and technical leaders
- Balance new AI-first capability development with modernization of mature enterprise SaaS systems, technical debt reduction, and continuity of existing customer commitments
- Improve measurable engineering outcomes, including delivery predictability, release quality, engineering productivity, modernization progress, and customer-impacting delivery velocity
- Contribute to planning, prioritization, resource allocation, and engineering investment tradeoff decisions in partnership with cross-functional stakeholders
- Ensure customer-facing SaaS capabilities are designed, delivered, and operated with strong standards for reliability, availability, scalability, performance, security, and quality
- Strengthen engineering practices across CI/CD, test automation, observability, operational readiness, incident learning, and continuous improvement
- Promote a production-first mindset that treats operability, supportability, resiliency, and cost efficiency as core design considerations
- Use engineering metrics and operational signals to identify systemic issues, improve team effectiveness, and guide technical and organizational improvements
- Lead through direct leadership accountability, senior technical credibility, and matrixed influence across Engineering, Product, Architecture, Business, and enabling functions
- Develop and mentor Directors, Senior Managers, Principal Engineers, and senior technical talent, building leadership capacity and raising the technical bar across teams
- Create a culture of ownership, accountability, constructive challenge, customer focus, innovation, and continuous learning
- Align globally distributed teams across time zones, cultures, and organizational boundaries
- Communicate clearly with executive, technical, and non-technical audiences, translating complex engineering topics into business-relevant decisions and outcomes
Skills
- Bachelor's degree in Computer Science, Engineering, or a related technical field
- 15+ years of progressive technology and software engineering leadership experience
- Proven experience leading and developing senior engineering leaders and technical leaders, including Directors, Senior Managers, Principal Engineers, or equivalent roles
- Demonstrated success leading engineering for customer-facing enterprise SaaS products, data-intensive platforms, analytics products, or comparable large-scale commercial software platforms
- Experience driving engineering transformation across mature SaaS environments, including modernization, technical debt reduction, quality improvement, and delivery acceleration
- Current experience leading AI-enabled product capability development within enterprise SaaS or comparable commercial software environments
- Experience applying GenAI tools and AI-assisted practices within engineering workflows to improve software delivery, quality, developer productivity, or modernization outcomes
- Experience leading globally distributed engineering teams in a matrixed organization
- Deep software engineering background with strong system design, distributed systems, and architecture experience
- Strong understanding of cloud-native architecture, scalable platform design, data-intensive systems, API design, integration patterns, performance optimization, reliability engineering, and enterprise architecture principles
- Prior hands-on engineering experience and leadership familiarity with technologies used by modern SaaS teams, including Java, Python, Angular, Azure cloud services, and AI/GenAI technologies and frameworks
- Ability to evaluate architectural options, challenge design assumptions, and guide technical tradeoffs across speed, quality, scalability, cost, security, maintainability, and customer impact
- Strong understanding of modern software development practices, including Agile delivery, CI/CD, automated testing, observability, secure engineering practices, and production operations
- Transformative mindset with the ability to move teams from established SaaS operating models toward AI-first product and engineering approaches
- Ability to challenge the status quo constructively, challenge self and teams to improve, and bring others along through influence, clarity, and technical credibility
- Strong executive presence, stakeholder management, and communication skills across technical and non-technical audiences
- High accountability for engineering outcomes, customer impact, and business-aligned execution
- Ability to operate effectively in ambiguity, make decisions with incomplete information, and create alignment across competing priorities
- Strong coaching and talent development skills, with a track record of building high-performing engineering leadership teams
- Experience leading AI-driven product transformation initiatives that created measurable customer value or commercial impact
- Experience with modern AI/GenAI application patterns, orchestration frameworks, model integration, retrieval-augmented generation, agentic workflows, or AI-enabled analytics experiences
- Experience in retail, CPG, consumer measurement, market intelligence, data analytics, or adjacent data-rich enterprise domains
- Background working in product-led technology organizations with close partnership across Product Management, Design, Architecture, Data Science, Security, and Business stakeholders
- Experience improving engineering operating models through metrics, platform thinking, engineering productivity practices, and production excellence
Benefits
- Flexible working environment
- Volunteer time off
- LinkedIn Learning
- Employee-Assistance-Program (EAP)
Company Overview
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