> Markdown version of [/jobs/ext/3085901-backend-engineer](https://www.wearedevelopers.com/jobs/ext/3085901-backend-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Backend Engineer - **Company:** Listitem - **Location:** Hamburg, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, BigQuery, Data Deduplication, Elasticsearch, Search Technologies, Data Streaming, TypeScript, Datadog, Large Language Models, Kotlin, Low Latency - **Published:** September 26, 2026 - **Apply:** https://startup.jobs/senior-backend-engineer-search-discovery-all-genders-about-you-se-co-kg-10195704 ## About the Role * 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 ## Description * 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Tomb rAIder: AI Search with Kotlin](https://www.wearedevelopers.com/videos/1989-tomb-raider-ai-search-with-kotlin) - [Kotlin Multiplatform - True power of native code reuse](https://www.wearedevelopers.com/videos/4-kotlin-multiplatform-true-power-of-native-code-reuse) - [Debugging in the Dark](https://www.wearedevelopers.com/videos/1658-debugging-in-the-dark) - [Software Engineering Social Connection: Yubo’s lean approach to scaling an 80M-user infrastructure](https://www.wearedevelopers.com/videos/1583-software-engineering-social-connection-yubo-s-lean-approach-to-scaling-an-80m-user-infrastructure) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Backend Developer Salary in Germany [2023]](https://www.wearedevelopers.com/magazine/196-backend-developer-salary-in-germany-2023) - [7 Most Popular Web Developer Jobs in Europe](https://www.wearedevelopers.com/magazine/163-7-most-popular-web-developer-jobs-in-europe)