Software Engineer – Adobe Experience Platform

Adobe Adobe · Enterprise · San Jose, CA

Senior Software Engineer role focused on architecting and scaling distributed systems for Adobe's Real-Time Customer Data Platform (RTCDP). The role involves integrating Generative AI/ML for personalization, building low-latency data pipelines, and developing cloud-native microservices. Emphasis on real-time data processing, identity resolution, and customer profiles at massive scale.

What you'd actually do

  1. Integrate cutting-edge Generative AI/ML into RTCDP for next-gen segmentation, recommendations, and live decisioning.
  2. Engineer resilient, high-throughput data flows with Kafka, Spark, Java/Scala to guarantee SLAs across diverse user journeys.
  3. Build and maintain mission-critical, cloud-native microservices supporting trillions of queries and activations.
  4. Lead project delivery from design through production, ensuring rigorous quality, performance, and measurable business results.
  5. Partner with product managers, designers, and data scientists to deliver privacy-first, customer-centric solutions that align with regulatory standards.

Skills

Required

  • 5+ years’ experience developing large-scale distributed systems or platforms in production environments.
  • Deep expertise in backend development (Java or Scala), with advanced skills in concurrency, performance tuning, and microservices.
  • Proven track record engineering real-time data solutions using event-driven architectures (Kafka, Spark/Flink).
  • Experience designing, implementing, and operating fault-tolerant, low-latency APIs in cloud-native settings.
  • Solid understanding of storage technologies (SQL, NoSQL, key-value stores).

Nice to have

  • Experience with customer data platforms, martech, adtech, or relevant verticals.
  • Background in identity resolution, segmentation, consent management, or privacy-first data architectures.
  • Hands-on with machine learning or personalization systems.
  • Working knowledge of regulatory compliance frameworks (GDPR, CCPA).
  • Demonstrated mentorship, leadership, and ability to shape architectural direction.

What the JD emphasized

  • ultra-low-latency pipelines
  • AI-driven personalization
  • real-time identity resolution
  • accurate customer profiles at massive scale
  • low-latency data pipelines
  • trillions of queries
  • critically important systems

Other signals

  • integrating generative AI/ML into RTCDP for next-gen segmentation, recommendations, and live decisioning
  • AI & Intelligence: OpenAI, Vector DBs, RAG architectures
  • Hands-on with machine learning or personalization systems