Senior Engineering Manager, Express AI Foundations

Adobe

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
San Jose, CA
Salary
$219,500–$317,775 / yr
Posted
2 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $214k
This role $269k
$164k most similar roles pay here $334k

This role pays more than 82% of similar roles. Most pay $180,262–$248,350 — the shaded band above. At the midpoint, this role pays about $269k versus about $214k for comparable roles.

Based on 240 similar postings.

Employer

About Adobe

Adobe Inc. is a global software company known for creative and multimedia software products including Photoshop, Illustrator, Acrobat, and its cloud-based Creative Cloud and Document Cloud suites. Industry: Creative & Digital Experience Software

Adobe currently has 218 open roles on FindRole.

Listed pay typically runs $187,100–$270,950 across 216 roles with salary data.

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At a glance

TL;DR · Senior Engineering Manager, Express AI Foundations

Senior Engineering Manager, Express AI Foundations joins the AI Foundations team to lead and grow a group of engineers building scalable infrastructure for Adobe Express. This role focuses on the end-to-end delivery of the AI stack, including Agentic, Imaging, Motion, and Personalization AI. You will manage the development of LLM orchestration, inference services, data pipelines, and evaluation frameworks while ensuring high standards for observability, fault tolerance, and responsible AI practices. The position requires expertise in distributed systems, MLOps, and large-scale service development to navigate complex technical trade-offs. You will collaborate with product and research teams to translate requirements into actionable roadmaps. Key skills include proficiency in prompt engineering, model registries, and data privacy protocols. You will manage a team of six to ten engineers, overseeing the full recruiting lifecycle and fostering professional growth within the organization.

What does a Engineering Manager earn in California?

Median $290250 from 64 postings across 19 companies.

See salary data

What you'll do

  • Own end-to-end delivery of AI infrastructure workstreams including LLM orchestration, inference services, and data pipelines.
  • Participate in system design reviews to challenge architectural decisions and unblock the team on complex technical problems.
  • Establish engineering quality standards for observability, fault tolerance, latency, security, and responsible AI practices.
  • Develop and communicate a coherent technical roadmap that balances immediate feature delivery with long-term architecture.
  • Translate high-level product requirements into concrete technical specifications, scoped workstreams, and prioritized project plans.
  • Collaborate with research and data science teams to integrate internal and third-party models into production systems.
  • Manage and coach a team of 6–10 engineers, providing regular feedback and career development support.
  • Lead the full recruiting lifecycle to hire and grow high-performing engineering talent for the organization.

What we're looking for

  • Must have 3–5 years of engineering management experience leading teams to deliver complex infrastructure or platform projects.
  • Requires a strong technical foundation in distributed systems, AI/ML infrastructure, or large-scale service development.
  • Must possess working fluency in modern AI/ML concepts including LLM orchestration, inference infrastructure, and data pipelines.
  • Must demonstrate the ability to coach, provide feedback, and manage career progression for engineers across various seniority levels.
  • Requires experience managing end-to-end execution, including structured prioritization, dependency management, and agile project delivery.
  • Must possess clear communication skills to translate technical trade-offs into business terms for non-technical stakeholders.
  • Preferred: A Master’s degree or equivalent experience in Computer Science, Machine Learning, or a related field.
  • Preferred: Experience with MLOps practices, Generative AI development, and responsible AI concerns like bias and data privacy.

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