Senior Software Engineering Manager

We are looking for a Senior Engineering Manager to lead our Landing Pages Platform team in Rome, who will be accountable for building and operating our next‑generation, AI‑ready landing page platform. You will own the technical direction and delivery of the experience layer that powers high‑traffic landing pages across paid and organic channels, ensuring reliable, high‑performing, and context‑aware customer experiences. In addition to driving system and API design for performance‑critical services, you will partner closely with Product, Marketing, Data, and Platform teams to turn search demand and experimentation opportunities into scalable landing experiences. As a people‑first leader, you will grow and support a high‑performing team of engineers, balancing rapid delivery with platform health, and long‑term sustainability, while fostering a culture of safe AI/ML adoption, experimentation, and strong engineering fundamentals.

In this role, you will:

• Lead multiple software engineering teams in designing, building, and operating highly available, performant, and secure services, including system design (LLD), API design, and data modeling for complex, customer‑facing capabilities.
• Define and drive the technical strategy and long‑term architecture for your area, aligning engineering decisions with business objectives and ensuring scalable, extensible, and resilient solutions across services and domains.
• Set engineering quality, reliability, and operational excellence standards, ensuring robust CI/CD practices, monitoring, alerting, and incident response processes are consistently applied across your teams.
• Hire, develop, and mentor engineers and managers, fostering a high‑performing, inclusive culture focused on learning, accountability, and effective collaboration with product, design, data, and other partner organizations.
• Safely integrate and operate AI/ML‑enabled solutions that improve outcomes, including familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products.
• Coordinate and prioritize delivery across multiple workstreams, managing dependencies, risks, and cross‑team integration to ensure coherent, timely delivery of end‑to‑end capabilities that can be adapted to multiple product and domain contexts.

Minimum Qualifications:

• Bachelor’s Degree or Equivalent Level; Technical Degree Preferred.
• 8+ years of relevant professional experience and 3+ years of people management experience.
• Experience managing engineering teams with end‑to‑end ownership of services or domains, including design, implementation, deployment, and ongoing operations for production services or multi‑service systems.
• Strong proficiency in core software engineering practices, including object‑oriented or functional programming, system design (LLD), API design, data modeling, testing strategies, and modern CI/CD pipelines.
• Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products, with the ability to guide teams in safely integrating and operating AI/ML‑enabled solutions.

Preferred Qualifications:

• Experience leading multiple engineering teams or a broad technical area, setting technical direction, and driving architecture decisions for distributed systems at scale.
• Demonstrated track record of improving system reliability, performance, and cost efficiency through data‑driven decision making, experimentation, and continuous optimization.
• Proven ability to lead complex cross‑team initiatives, align stakeholders across product and engineering, and deliver integrated solutions that span multiple services or domains.
• Experience defining and enforcing engineering standards for operational excellence, including observability, incident management, on‑call practices, and post‑incident learning. xysqume
• Advanced experience with safely integrating AI/ML‑enabled capabilities into production systems at scale (such as personalization, ranking, recommendations, or intelligent automation), including governance, evaluation, and ongoing model‑driven feature iteration, and providing strategic leadership on where and how to apply AI within your product and platform area.

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