Sr Engineering Manager, AI Platform

Adobe Adobe · Enterprise · San Jose, CA +2

Senior Engineering Manager to lead teams building and evolving the Adobe Firefly AI Platform, focusing on large-scale model training, fine-tuning, inference, and serving infrastructure for generative AI products. The role involves technical leadership, architectural decisions, and team management to ensure cost efficiency, performance, and reliability.

What you'd actually do

  1. Lead and develop a high-performing engineering team responsible for designing and delivering modern AI platforms that support generative AI model training, fine-tuning, evaluation, and production-grade applications.
  2. Partner closely with product management and customer stakeholders to shape the product roadmap, define user experiences, and align priorities, milestones, and release strategies. Coordinate effectively with upstream and downstream technical teams to ensure seamless integration.
  3. Own the full platform product lifecycle, from planning and architecture through development, rollout, and post-launch impact analysis. Drive execution accountability, proactively identify risks and opportunities, and remove barriers to maintain momentum.
  4. Provide hands-on technical leadership across system architecture, design reviews, and operational frameworks. Ensure platform components are secure, scalable, performant, and resilient, while balancing short-term delivery needs with long-term platform health.
  5. Build and sustain a strong engineering culture centered on collaboration, psychological safety, and continuous improvement. Recruit, mentor, and retain exceptional engineering talent, and guide team members in both their professional and personal growth.

Skills

Required

  • BS or higher in Computer Science or a related technical field, or equivalent practical experience
  • At least 10 years of professional software engineering experience
  • Prior experience managing engineering teams
  • Demonstrated ability to lead distributed teams
  • Collaborate effectively across time zones, work styles, and cultures
  • Strong analytical decision-making skills
  • Ability to navigate ambiguity
  • Establish priorities
  • Drive clarity by leveraging quantitative insights
  • Proven success in developing, coaching, and empowering software engineers
  • Cultivating an environment that supports growth, accountability, and high performance

What the JD emphasized

  • large-scale model training
  • fine-tuning
  • inference and serving infrastructure
  • generative AI products
  • AI infrastructure
  • production-grade applications
  • platform product lifecycle
  • system architecture
  • operational frameworks
  • engineering culture

Other signals

  • large-scale model training
  • fine-tuning
  • inference and serving infrastructure
  • generative AI products
  • AI infrastructure