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# Director of Engineering - Machine Learning & AI Products

- **Company:** Adobe Inc.
- **Location:** San Jose, CA, United States
- **Salary:** $265,700.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software Documentation, Machine Learning, Software Engineering, Systems Integration, Large Language Models, Build Management
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/director-of-engineering-machine-learning-ai-products-san-jose-ca--85ee48f9-8436-406e-9f13-c26fe7e2efb0

## About the Role

Machine Learning, Artificial Intelligence (AI), Machine Learning, Artificial Intelligence (AI), System Lifecycle, Production Machining, User Documentation, Leadership, Performance Modeling, Product Development, * Over 15 years of experience in software engineering, with extensive expertise in machine learning or systems driven by artificial intelligence.

 * Demonstrated history of delivering and managing AI/ML products in production, beyond just experimentation or research.
 * Strong business and commercial exposure, with direct ownership or leadership of a customer-facing, revenue-impacting AI/ML product.
 * Strong experience with ML system build, production architecture, and real-world operational challenges.
 * Demonstrated success leading senior technical teams, including performance evaluations, mentoring, and org scaling.
 * Ability to engage deeply with product partners and debate technical and product tradeoffs in fast paced environments.
 * Experience working directly with external customers and understanding customer-facing production realities.

Preferred Background

 * Proven track record of building AI/ML products in startup or startup-like contexts that prioritize rapid market introduction.
 * Background in external, customer-facing platforms or products, particularly AI-first offerings.
 * Familiarity with domains such as marketing technology, sales technology, or customer experience platforms.

Leadership Attributes We Value

 * Hands-on, credible technical leadership with the ability to go deep when needed.
 * Strong product intuition paired with engineering rigor.
 * Comfort operating in ambiguity while building structure for scale.
 * Ability to earn trust quickly with senior engineers, product leaders, and customers.

## Description

We are looking for a Director of Engineering to guide the development of AI-native, production-ready machine learning products for external clients. This leader will be responsible for the entire lifecycle of sophisticated AI systems-from product conception and rollout to production, customer engagement, and continuous operational success.

This role requires a rare blend of hands-on technical depth, product judgment, and senior-level people leadership. You will lead a highly experienced ML engineering organization and work closely with Product, Development, and Go-to-Market partners to bring differentiated AI solutions to market.

Key Responsibilities

Technical & Product Leadership

 * Own the end-to-end delivery of AI/ML solutions deployed in production, moving beyond proofs-of-concept to scalable, reliable, customer-facing systems.
 * Lead deep technical discussions on system build, model integration, performance, reliability, and operational readiness.
 * Collaborate directly with Product Management to build product vision, challenge assumptions, and ensure differentiation beyond general-purpose LLM capabilities.
 * Drive architectural decisions that balance innovation, scalability, cost, and long-term maintainability.
 * Act as a senior technical voice with customers, handling partner concerns, roadmap discussions, and production issue resolution.

Team & Organizational Leadership

 * Establish, grow, and manage a high-caliber ML engineering organization, scaling the team from about 4 to over 20 engineers as time progresses.
 * Manage and mentor senior engineers and leaders with 16+ years of experience, encouraging accountability, ownership, and continuous growth.
 * Establish a flat, hands-on, hybrid operating model where leaders stay close to the work while empowering teams to implement initiatives independently.
 * Conduct performance management, career development, and succession planning aligned to director-level expectations.

Execution & Operations

 * Ensure excellence in production operations, including monitoring, incident response, model performance, and customer-reported issues.
 * Drive strong engineering rigor across testing, release readiness, and post-launch support.
 * Build scalable processes that support rapid iteration while maintaining enterprise-grade reliability.