Director of Engineering – Machine Learning & AI Products
AdobeSan JosePosted 1 March 2026
Tech Stack
Job Description
The Opportunity 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. Required Qualifications 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. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences ... (truncated, view full listing at source)
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