Staff Machine Learning Engineer, Adobe GenStudio

What You Will Do As an AI Manager at Adobe within GenStudio, you'll lead, empower, and expand a high‑performing engineering team focused on building next‑generation AI‑enabled web and marketing solutions. You will bring strategic AI leadership alongside deep engineering guidance, partnering closely with product, design, and operations to deliver innovative, scalable, and user‑centric experiences that drive performance marketing success for Adobe's customers. Your role will include: Leadership & Team Development Inspire and guide a team of full‑stack engineers in architecting cutting‑edge web applications with integrated generative AI capabilities. Cultivate a culture of collaboration, psychological safety, continuous learning, experimentation, and a bias toward shipping. Mentor engineers in both technical craft and AI fluency; helping them grow in areas such as model integration, prompt engineering, agentic system design, and data‑driven UX. Lead AI‑specific performance development cycles, career planning, and skills roadmaps. Technical & AI Strategy Drive the technical vision for how generative AI is incorporated into customer‑facing products, balancing creativity, performance, reliability, and responsible AI principles. Partner with product and design teams to move quickly from idea to production — selecting the right models, iterating fast, and shipping with confidence. Establish best practices for integrating LLMs, agents, evals, embeddings, and real‑time AI services into front‑end and backend stacks. Oversee architectural decisions that ensure reliability, scalability, and responsiveness of AI‑powered experiences. Cross‑Functional Collaboration Work closely with Product, Design, and Go‑to‑Market teams to translate strategic objectives into prioritized engineering and AI deliverables. Serve as a key contributor in cross‑disciplinary planning sessions that align AI use cases with Adobe GenStudio's roadmap. Advocate for user‑centered design, accessibility standards, and performance optimization throughout the development lifecycle. Process & Quality Champion engineering excellence through thoughtful code reviews, architectural discussions, and quality assurance practices. Implement processes that improve team velocity, delivery predictability, and operational visibility. Drive the adoption of AI development tools, agent evaluation frameworks, CI/CD for AI applications, observability frameworks, and secure cloud workflows. Experience & Qualifications Technical Leadership: 5 years of strong engineering experience with modern web technologies (HTML, CSS, JavaScript/TypeScript, React or similar). Proven track record guiding engineering teams and delivering production‑quality software. AI & Generative Technology: Hands‑on experience developing, integrating, or shipping products with generative AI, large language models (LLMs), or agentic systems. Familiarity with prompt engineering, eval frameworks, and AI‑centric software architecture. Architectural Fluency: Understanding of front‑end/build tools, REST/GraphQL APIs, and experience with cloud environments (AWS, Azure, or GCP). System Thinking: Able to assess trade‑offs in performance, maintainability, and scalability; comfortable defining patterns for async data flows, client–server interactions, and AI service orchestration. Process & People Skills: Experience establishing standards, leading cross‑functional teams, and elevating engineering practices. Strong mentorship and communication skills. AI Product Mindset: Demonstrated ability to shape AI features that are usable, transparent, safe, inclusive, and aligned to customer needs. Personal Profile A people‑centric leader who fosters psychological safety, inclusion, and innovation. A strategic thinker who balances long‑term technical vision with tactical execution. Passionate about generative AI and its responsible application in real‑world products. A builder at heart; energized by turning ideas ... (truncated, view full listing at source)