Senior Software Engineer - Experience League Knowledge Platform & GenAI Services

Our team’s charter is evolving from building a single product surface to delivering GenAI-first Knowledge Services -reliable, scalable platform capabilities that expose Experience League content as trusted, structured, and AI-ready knowledge for internal and external clients. We are looking for a Senior Software Engineer (P40) who will help design and build these knowledge management and GenAI services , enabling product teams to create high-quality, agentic product knowledge experiences without relying on ad-hoc ingestion or scraping approaches. What You’ll Do

• Design and build backend services and APIs that expose Experience League content as a managed knowledge platform for downstream consumers such as product knowledge agents and AI Assistant.
• Replace ad-hoc content ingestion approaches with scalable, governed knowledge access patterns suitable for agentic workflows.
• Build and operate knowledge management services , including metadata, taxonomy, and structured representations (such as knowledge graphs ), to improve retrieval quality for AI agents and assistants.
• Build services that support agentic workflows , including content retrieval, enrichment, versioning, feedback loops, and quality signals used by AI agents.
• Evolve the content publishing pipeline to make Experience League content AI-ready by design , supporting structured data, tagging, and faster availability for GenAI consumers.
• Take ownership of ambiguous, cross-cutting problem spaces in knowledge and GenAI platforms, shaping solutions from early design through production adoption.
• Raise the operational bar for shared GenAI and knowledge services through automation, monitoring, and incident learning.
• Improve the scalability, reliability, and maintainability of systems that transform authored content into consumable knowledge assets.
• Apply CDN expertise to ensure globally distributed, low-latency access to knowledge content for both human and machine consumers.
• Build and operate containerized services using Docker and Kubernetes , applying cloud-native patterns for resilience, observability, and safe deployment.
• Influence adoption of shared knowledge and GenAI services by working closely with product, content, and platform teams to define clear integration patterns and success metrics., If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs. Massachusetts: Massachusetts Legal Notice It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Internal Opportunities Creativity, curiosity, and constant learning are celebrated aspects of your career growth journey. We’re glad that you’re pursuing a new opportunity at Adobe! Put your best foot forward:

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• 6+ years of professional software engineering experience , including hands-on experience delivering GenAI-powered services used by other teams , with exposure to agent-based or retrieval-augmented (RAG-style) workflows.
• Senior-level experience building and operating large-scale backend or platform services , with strong ownership of reliability and performance.
• Practical understanding of GenAI production concerns , including evaluation, quality, observability, safety, and cost trade-offs.
• Strong hands-on expertise with backend services and API design.
• Production experience with Kubernetes, Docker, and MongoDB Atlas , including schema design, indexing, and performance tuning.

• Ability to work across teams and influence platform adoption through clear communication and technical leadership. Nice to Have

• Experience building knowledge management systems or content platforms used by both humans and AI.
• Experience integrating with AEM / EDS or large-scale content authoring systems.
• Experience with CDN-based optimization strategies for globally distributed content delivery.
• Familiarity with shared GenAI service models , such as service catalogs, onboarding patterns, or governance frameworks.

You will help transform Experience League from a content destination into a foundational knowledge platform , powering agentic product knowledge experiences across Adobe. Your work will reduce duplicated ingestion efforts, raise the quality and reliability of AI-powered knowledge, and accelerate how teams build and ship GenAI experiences. 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 $139,000 – $257,550 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 $177,900 - $257,550 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. State-Specific Notices: California : Fair Chance Ordinances Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances. Colorado

Experience League is Adobe’s enterprise learning and enablement platform , powering documentation, communities, events, and support experiences across a global audience. Increasingly, this content is not only consumed by humans, but also by AI systems that power knowledge agents and agentic workflows.