Senior Software Engineer - Experience League Knowledge Platform & GenAI Services
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Job description
Our team's charter is evolving from building a single product surface to delivering GenAIfirst Knowledge Services-reliable, scalable platform capabilities that expose Experience League content as trusted, structured, and AIready 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 highquality, agentic product knowledge experiences without relying on adhoc 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 adhoc 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 AIready by design, supporting structured data, tagging, and faster availability for GenAI consumers.
- Take ownership of ambiguous, crosscutting 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, lowlatency access to knowledge content for both human and machine consumers.
- Build and operate containerized services using Docker and Kubernetes, applying cloudnative 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.
Requirements
- 6+ years of professional software engineering experience, including handson experience delivering GenAIpowered services used by other teams, with exposure to agentbased or retrievalaugmented (RAGstyle) workflows.
- Seniorlevel experience building and operating largescale backend or platform services, with strong ownership of reliability and performance.
- Practical understanding of GenAI production concerns, including evaluation, quality, observability, safety, and cost tradeoffs.
- Strong handson 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 largescale content authoring systems.
- Experience with CDNbased optimization strategies for globally distributed content delivery.
- Familiarity with shared GenAI service models, such as service catalogs, onboarding patterns, or governance frameworks.
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 $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.