Sr Clojure Backend Software Engineer
NirYu
- AI-ML-Engineering
- Backend-Engineering
- Clojure
- Developer
- Senior-Clojure-Backend-Engineer
- Senior-Clojure-Developer
- Software-Engineer
- Software-Engineering
Assessed from original listing evidence
The role
Job description
The Role:
We are looking for a skilled Clojure Backend Software Engineer for the Core Outfitting team. The main goal of this role is to build and scale the AI-powered infrastructure and workflows that generate outfit images, styled bundles, "Complete the Look" recommendations, and vector search features powering 175+ enterprise retailers and over 100M+ monthly shoppers.
While you will touch Clojure and ClojureScript across the stack, this is a backend-heavy role. Responsibilities include designing PostgreSQL schemas, integrating with LLM APIs (GPT, Gemini), orchestrating multi-step workflows using Temporal, implementing RAG pipelines with Qdrant, and building internal human-in-the-loop review interfaces in ClojureScript (re-frame).
Must-Have Qualifications:
Education: Bachelor’s Degree in Computer Science, Software Engineering, or related fields.
Clojure / ClojureScript Expertise: Strong production experience with Clojure, deep functional programming understanding, and comfort within the ecosystem (shadow-cljs, re-frame, reagent).
Databases & SQL: Solid experience modeling complex domains, designing schemas, writing optimized queries, and managing migrations in PostgreSQL.
LLM & AI Practical Knowledge: Hands-on experience working with LLM APIs, prompt engineering, context windows, and managing non-deterministic outputs in production.
Collaborative Mindset: High-energy team player who thrives on real-time architecture debates and solving technical problems "out loud."
Advanced English: Fluency in communicating complex technical designs and participating in live engineering syncs.
Nice-to-Have Skills:
Experience with Temporal or similar workflow orchestrators (Airflow, Step Functions).
Experience with vector databases (Qdrant, Pinecone, Weaviate) and RAG architectures.
Knowledge of image generation, multimodal AI models, or MCP (Model Context Protocol).
Originally posted on Himalayas
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