The company is partnering with a leading retail AI company that provides scalable, AI-driven solutions for product enrichment, styling, and discovery. Their technology transforms retail data into rich, structured content that enhances customer engagement and drives sales across e-commerce, apps, and in-store experiences for millions of shoppers worldwide. We are seeking passionate Senior Clojure Engineers to join our remote-first team and help build the future of AI-powered fashion and retail automation. This role is perfect for engineers who thrive in functional programming, value ownership, and want to create impactful systems that scale to millions of users.<\/p>\n\n\n\n
Responsibilities:<\/strong> Requisitos:<\/strong> Preferred:<\/strong>
\u25cf Design and implement Temporal workflows that orchestrate multi-step AI operations, including product attribution, description generation, metadata enrichment, laydown image creation, outfit creation, and feed optimization for platforms like Google Merchant Center and other shopping networks.
\u25cf Develop backend services in Clojure that integrate with LLM APIs (GPT, Gemini, etc.), managing context, prompts, and streaming responses, as well as processing structured outputs for various AI driven features.
\u25cf Build and maintain data models and PostgreSQL schemas that support complex enrichment pipelines, product taxonomies, attribute hierarchies, vector embeddings, and seamless integration with retailer catalog systems.
\u25cf Create RAG pipelines using Qdrant for semantic search, product similarity matching, and context retrieval to enable more accurate attribute inference and enrichment suggestions.
\u25cf Develop APIs and data pipelines that deliver enriched catalogs and product data to retailer PDPs, shopping feeds, and search engines, ensuring reliable data flow and performance.
\u25cf Design ClojureScript UIs for review workflows where humans validate, edit, and improve AI generated content, facilitating collaboration between AI and human validation.
\u25cf Implement monitoring systems to track AI quality, coverage, and downstream performance, ensuring robust and reliable AI operations.<\/p>\n\n\n\n
\u25cf Bachelor’s Degree in Computer Science, Software Engineering, or related fields.
\u25cf Strong Clojure and ClojureScript experience, with a proven track record of building production systems. You understand functional programming deeply and are comfortable with the ecosystem (shadow-cljs, re-frame, reagent, etc.).
\u25cf Solid SQL skills and database design experience \u2014 modeling complex domains in PostgreSQL, writing efficient queries, designing schemas, and managing migrations.
\u25cf Experience integrating LLMs into production systems: prompt engineering, managing context windows, handling non-deterministic outputs, and building reliable AI features.
\u25cf Backend engineering fundamentals: building APIs, designing data flows, error handling, and scalable system architecture.
\u25cf High velocity: shipping often, balancing speed with quality, knowing when to refactor or iterate, and delivering value quickly.
\u25cf Ownership mindset: taking responsibility for features from conception to deployment, caring about outcomes.
\u25cf An interest in AI, workflow orchestration, vector search, data modeling, and how all pieces fit together.
\u25cf Confident communication (written and oral) skills and a demonstrated ability to work collaboratively with all levels of internal and external organizations
\u25cf Advanced English level.
\u25cf Based in LATAM.<\/p>\n\n\n\n
\u25cf Experience with Java and the JVM ecosystem.
\u25cf Experience with Temporal or similar workflow orchestration systems (Airflow, Dagster, Step Functions).
\u25cf Familiarity with vector databases like Qdrant, Pinecone, or Weaviate, and RAG architectures.
\u25cf Experience with MCP (Model Context Protocol) or building tool-calling systems where LLMs interact with external services.
\u25cf Experience with front-end development and ClojureScript, particularly in building UI tools for workflows.
\u25cf Background in product catalog systems, taxonomies, or PIM platforms.
\u25cf Knowledge of SEO, structured data (schema.org), or feed management (Google Merchant Center).
\u25cf Experience with large-scale data transformation, normalization, or data quality pipelines.
\u25cf Background in other functional languages (Haskell, OCaml, Elixir, Scala).
\u25cf Experience building developer tools, automation systems, or human-in-the-loop workflows.
\u25cf Experience at high-growth startups and comfort working in dynamic environments.<\/p>\n\n\n\n