Agentic Outcome Engineer (Customer AI Solution Engineer)

Role summary As an Agentic Outcome Engineer (Customer AI Solution Engineer), you will work directly with customers to turn agentic AI capabilities into useful, reliable, production-ready outcomes. You will connect business goals to technical implementation—scoping workflows, configuring and validating agent-powered solutions, resolving delivery challenges, and helping customers realize ongoing value. You will partner across customer teams, Product, Engineering, Sales, and Customer Success. This role combines hands-on technical delivery with customer communication, practical problem-solving, and a focus on measurable results. What you’ll do • Work with customers to understand their goals, current workflows, constraints, and desired outcomes. • Identify suitable agentic use cases and translate them into scoped plans, success criteria, and implementation steps. • Configure and operate agent-powered workflows, including relevant tools, skills, data, context, and integrations. • Guide implementations from discovery and planning through testing, launch, knowledge transfer, and ongoing improvement. • Validate agent outputs and workflow behavior for quality, reliability, and fit to customer requirements; involve human review where appropriate. • Fix technical issues across configuration, data flows, access, integrations, and connected systems; coordinate customer concerns with the right teams. • Monitor adoption and outcome measures, identify improvement opportunities, and help customers increase value over time. • Coordinate work across customer collaborators and Adobe’s Product, Engineering, Sales, and Customer Success teams. • Share customer feedback, recurring issues, and product gaps with internal teams. • Create and maintain reusable documentation, implementation patterns, and automation that improve delivery. What you’ll bring • Experience in software engineering, solutions engineering, technical consulting, implementation, or a similar customer-facing technical role. • Hands-on familiarity with generative AI or agentic systems, such as LLM-powered workflows, tool use, orchestration, or AI-assisted automation. • Ability to investigate technical issues using APIs, logs, configuration, and structured problem solving. • Experience integrating cloud software with customer data, services, or business workflows. • A practical understanding of testing and evaluating AI-assisted systems, including output quality, reliability, and appropriate human oversight. • Awareness of security, privacy, access control, and governance considerations when working with customer systems and data. • Native-level Japanese and business-level English proficiency, with the ability to explain technical concepts clearly, engage effectively with customers, and collaborate across global teams. • A delivery approach: able to prioritize, make progress with incomplete information, and connect technical work to customer outcomes. ] Helpful additional experience • Experience with Adobe products or platforms relevant to the role. • Experience in customer onboarding, production deployment, technical account support, or managed services. • Familiarity with workflow automation, cloud platforms, data pipelines, observability, or AI evaluation frameworks. • Domain expertise aligned to the assigned product area—for example, AEM and Edge Delivery Services migration, or SEO/GEO, CDN configuration, and digital brand visibility. How success is measured • Customers achieve agreed outcomes and reach production use effectively. • Agent-powered workflows meet agreed expectations for quality, reliability, and safe operation. • Customers adopt the solution and continue to realize value after initial implementation. • Technical blockers are resolved or brou