Senior Manager - Software Engineering

Job Title

Senior Manager - Software Engineering (AI Tooling & Quality Engineering Platforms)

Global Quality Engineering (GQE)

New York City, Los Angeles, San Francisco

Paramount Skydance Corp. is seeking a Senior Manager, Software Engineering to lead a team of engineers building AI‑powered tooling, internal platforms, and intelligent automation systems that support the Global Quality Engineering organization. This is not an “in test” role — your team will build production‑grade software, AI platforms, and developer tools that transform how GQE engineers test, triage, analyze, and deliver quality at scale.

You will manage a team that includes Software Engineers, Senior Engineers, Staff Engineers, and potentially a Principal Engineer. You will provide technical direction, drive execution, develop talent, and partner with cross‑functional leaders to deliver high‑impact AI capabilities across brands and engineering pillars. This role requires a blend of proficient engineering leadership, architectural judgment, people management, and the ability to drive organizational change through AI‑enabled tooling.

• Lead, mentor, and grow a high‑performing engineering team responsible for AI tooling and internal platforms.
• Provide coaching, career development, and performance management for engineers across multiple levels.
• Foster a culture of technical excellence, psychological safety, and continuous improvement.
• Drive hiring, onboarding, and talent development to scale the team successfully.
• Define and execute the roadmap for AI‑enabled quality engineering tools and platforms.
• Partner with Principal and Staff Engineers to set architectural direction and ensure technical rigor.
• Oversee delivery of AI‑powered services, RAG pipelines, developer tools, and automation accelerators.
• Ensure systems are reliable, scalable, observable, and aligned with enterprise engineering standards.
• Collaborate with QE leadership, Platform Engineering, Data Engineering, Playback/Video Engineering, and Product to identify high‑value opportunities for AI tooling.
• Translate organizational needs into clear technical requirements and team priorities.
• Communicate progress, risks, and outcomes to senior leadership with clarity and precision.
• Establish engineering best practices, coding standards, and quality gates for the team.
• Ensure predictable delivery through effective planning, estimation, and execution.
• Drive continuous improvement in development velocity, reliability, and operational maturity.
• Manage budgets, vendor relationships, and resource allocation as needed.

• 6+ years of software engineering experience, including 3+ years managing engineers or leading teams.
• Strong background in backend engineering, distributed systems, or platform development.
• Experience building or overseeing AI‑powered systems (LLMs, RAG pipelines, embeddings, automation accelerators).
• Demonstrated ability to lead teams delivering production‑grade internal tools or platforms.
• Strong communication skills and ability to influence across engineering and product organizations.
• Experience with cloud platforms (AWS, GCP, Azure), Kubernetes, and modern CI/CD practices.

• Experience managing teams that build internal developer platforms or productivity tooling.
• Familiarity with quality engineering workflows, automation frameworks, or large‑scale testing systems.
• Experience working in media/streaming, distributed playback systems, or device‑level environments.
• Prior experience partnering with Staff/Principal engineers to drive architectural strategy.

• People Leadership – develops talent, builds proficient teams, and drives accountability.
• Technical Judgment – makes sound architectural decisions and guides engineers successfully.
• Strategic Thinking – aligns team execution with organizational priorities and long‑term vision.
• Cross‑Functional Influence – builds trust and alignment across engineering, product, and QE.
• Operational Excellence – ensures predictable delivery, reliability, and continuous improvement.
• AI Fluency – understands where AI adds value and how to operationalize it at scale.