Director of Engineering - Machine Learning & AI Products
Role details
Job location
Tech stack
Job 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 handson technical depth, product judgment, and seniorlevel people leadership. You will lead a highly experienced ML engineering organization and work closely with Product, Development, and GotoMarket partners to bring differentiated AI solutions to market. Key Responsibilities Technical & Product Leadership
- Own the endtoend delivery of AI/ML solutions deployed in production, moving beyond proofsofconcept to scalable, reliable, customerfacing 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 generalpurpose LLM capabilities.
- Drive architectural decisions that balance innovation, scalability, cost, and longterm 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, handson, 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 directorlevel expectations.
Execution & Operations
- Ensure excellence in production operations, including monitoring, incident response, model performance, and customerreported issues.
- Drive strong engineering rigor across testing, release readiness, and postlaunch support.
- Build scalable processes that support rapid iteration while maintaining enterprisegrade reliability.
Requirements
- 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 realworld 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 customerfacing 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, customerfacing platforms or products, particularly AIfirst offerings.
- Familiarity with domains such as marketing technology, sales technology, or customer experience platforms.
Leadership Attributes We Value
- Handson, 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.
Benefits & conditions
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.
At Adobe, we empower employees to innovate with AI - and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it's restricted during live interviews. See how we think about AI in the hiring experience.
Expected Pay Range: Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this positionis $206,400 -- $384,675 annually. Paywithin this range varies by work locationand may also depend on job-related knowledge, skills,and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. In California, the pay range for this position is $265,700 - $384,675
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.