Senior Backend Engineer - Search & Discovery (all genders)

Develop the search engine behind ABOUT YOU, covering query understanding, entity resolution, and semantic vector search in Node.js/TypeScript
Blend OpenSearch relevance, embedding similarity, and behavioral re-ranking signals into unified search results
Build search-index pipelines (entities, synonyms, k-NN product vectors) streaming data from BigQuery into OpenSearch
Integrate LLMs and embedding models (Gemini, Vertex AI) under tight latency budgets with caching and fallback layers
Guard search relevance using golden lists, regression suites, and continuous A/B experiments
Shape architecture alongside our Tech Lead and collaborate closely with data analysts, engineers, and product managers
You love investigating the "why" behind search outcomes and turning those findings into actionable technical improvements
5+ years of experience building scalable, low-latency backend APIs (Node.js/TypeScript preferred, or fast-converting from Java, Go, or Kotlin)
Real depth in Elasticsearch/OpenSearch (mappings, custom analyzers, percolators, scoring functions) beyond just basic query clients
Strong algorithmic intuition for ranked data (merging, deduplication, score blending, and latency trade-offs)
You're excited to bridge backend engineering and ML by serving model scores, embeddings, or LLM features in production
Fluent English communication skills and a pragmatic, data-curious mindset
Nice to Have
IR/NLP fundamentals (tokenization, multilingual search, relevance evaluation frameworks)
Vector search experience (k-NN/HNSW indices, SigLIP embeddings, recall vs. latency tuning)
LLM engineering (prompt caching, timeout budgets, Datadog LLM Observability)
Familiarity with BigQuery, dbt, or Dagster pipelines

Employment type
Full-time

Work arrangement
Hybrid