Sr Computer Scientist 2

Adobe Adobe · Enterprise · Noida, India

Senior Computer Scientist at Adobe to define technical direction for hybrid search and AI assistant features across Adobe's C&P interfaces. The role involves owning the architecture for indexing, query processing, ranking, and recommendations, including ML-based ranking and assistant workflows, scaling to billions of assets in real time. The position requires setting direction for platform evolution, benchmarking new approaches, and making build-vs-buy decisions, including where generative AI can replace older methods. The role also emphasizes the daily use of AI coding agents and LLM-assisted workflows for development, testing, and documentation, and mentoring engineers on distributed systems, search expertise, and AI-assisted development.

What you'd actually do

  1. Define the technical direction for hybrid search and AI assistant features throughout Adobe's C&P interfaces. Develop a unified method that functions effectively across different surfaces with varied data models and usage behaviors.
  2. Own the architecture for indexing, query processing, ranking, and recommendations, including ML-based ranking and assistant workflows. Scale to billions of assets in real time.
  3. Set direction for platform evolution: benchmark new approaches to relevance, latency, and cost, and make build-vs-buy calls, including where generative AI can replace older methods.
  4. Employ AI coding agents (such as Claude Code) and LLM-assisted workflows routinely for development, testing, and documentation. Encourage widespread usage across teams.
  5. Set and enforce engineering standards (build reviews, code quality, performance benchmarks). Mentor engineers on distributed systems, search expertise, and AI-assisted development.

Skills

Required

  • Java
  • Python
  • stream processing (Kafka, Storm, Hadoop, Spark)
  • large-scale ingestion/indexing pipelines
  • REST/web services architecture
  • AWS infrastructure
  • Elasticsearch/Solr
  • distributed systems
  • search internals (inverted indexes, query processing)

Nice to have

  • semantic search
  • AI assistant experience
  • embeddings
  • vector search
  • RAG
  • agentic build
  • RDBMS/NoSQL data modeling

What the JD emphasized

  • 13+ years of industry experience, with a track record of owning architecture for large-scale, production distributed systems.
  • Proven experience setting technical direction across product areas with different data structures and customer needs.
  • Comfort acting as the lead technical expert alongside Product and Applied Research/ML teams, and turning early-stage research into production architecture.
  • Deep hands-on skills in Java and/or Python, stream processing (Kafka, Storm, Hadoop, Spark), and large-scale ingestion/indexing pipelines in production.
  • Strong background in REST/web services architecture and AWS infrastructure (compute, storage, messaging, scaling).
  • Substantial Elasticsearch/Solr experience: index build, sharding strategy, cluster architecture at scale, and a solid grasp of search internals like inverted indexes and query processing.

Other signals

  • building generative AI engine
  • ML-powered search
  • AI assistant functions
  • orchestration
  • real-time systems