Senior Software Engineer — GenAI Platform

Senior Software Engineer - Experience League Knowledge Platform & GenAI Services

The Opportunity
Experience League is Adobe's enterprise learning and enablement platform, powering documentation, communities, events, and support experiences across a global audience. Content is increasingly consumed by humans and by AI systems that power knowledge agents and agentic workflows. Our team's charter evolves 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) to design and build knowledge management and GenAI services that enable product teams to create high‑quality, agentic product knowledge experiences without relying on ad‑hoc ingestion or scraping approaches.

• 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 assistants.
• 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.

• 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 tradeoffs.
• Strong hands‑on expertise with backend services and API design.
• Production experience with Kubernetes, Docker, and Mongo
  
  DB Atlas, including schema design, indexing, and performance tuning.
• Ability to work across teams and influence platform adoption through clear communication and technical leadership.

• 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…