Software Engineer, AI Search Platform

As a Software Engineer, AI Search Platform, you will help evaluate and build the next-generation keyword search platform for a high-scale retail and digital commerce environment.

The initial focus will be a MongoDB Atlas Search POC because product, availability, and regional data already live close to MongoDB. You will validate whether MongoDB Atlas Search can meet current production search expectations while also helping compare other Lucene-based options such as AWS OpenSearch, Elasticsearch, or similar technologies if needed.

The ideal candidate is a senior or strong mid-level engineer with hands-on experience building or tuning Apache Lucene-based search platforms, such as MongoDB Atlas Search, AWS OpenSearch, Elasticsearch, or similar technologies. They can independently drive a search migration POC, evaluate relevance quality, design indexing and comparison flows, and partner across Product, Analytics, and Engineering to recommend a production migration path.

Responsibilities

· Build and evaluate search platform capabilities for keyword search migration, relevance tuning, indexing, ranking, and search-quality measurement.

· Design MongoDB Atlas Search indexes, analyzers, schemas, ranking signals, and query patterns for product search use cases.

· Develop backend APIs and services using Node.js, Java, and Python to support search workflows, indexing, evaluation, and observability.

· Design a production-safe shadow evaluation flow that samples a small percentage of search traffic, captures query context and production baseline results, and compares candidate search output outside the customer-facing request path.

· Evaluate autocomplete, query suggestions, popular searches, top results, zero-result behavior, fuzzy matching, synonym handling, regional ranking, merchandising behavior, and availability-aware ranking.

· Partner with Product, Analytics, and business stakeholders to define and measure search migration KPIs, including relevance quality, latency, add-to-cart impact, conversion impact, and regional availability behavior.

· Build and tune BM25/Lucene-based search indexes, analyzers, ranking signals, and retrieval pipelines.

· Contribute to the longer-term search platform roadmap, including automated chunking, indexing, BM25-based retrieval, hybrid search, and search-driven AI workflows.

· Write maintainable code, tests, documentation, and operational notes that help the platform scale beyond the POC.

· 4+ years of professional software engineering experience.

· Hands-on experience designing, tuning, and evaluating keyword-search relevance using Lucene/BM25-style retrieval, analyzers, tokenization, synonyms, fuzzy matching, boosts, ranking signals, and result-quality evaluation.

· Experience building backend APIs, REST services, and service-to-service workflows using Node.js, Java, and/or Python.

· Experience designing search schemas, indexes, incremental indexing flows, and query/relevance evaluation pipelines.

· Working knowledge of MongoDB or similar document/database systems.

· Experience with production observability, including logs, metrics, traces, latency measurement, and quality comparison dashboards.

· Familiarity with Docker, CI/CD, Git, automated testing, and modern software delivery practices.

· Ability to work with ambiguous requirements and translate business search goals into practical engineering plans.

Preferred Qualifications

· Experience with Lucene-based search platforms is preferred, including MongoDB Atlas Search, AWS OpenSearch, Elasticsearch, or similar technologies. The initial POC will focus on MongoDB Atlas Search. Elasticsearch experience is helpful but not required.

· Experience with retail, e-commerce, marketplace, or product-search systems is strongly preferred.

· Experience with product availability, regional/store context, ranking experiments, merchandising signals, autocomplete, query suggestions, or conversion-focused search optimization.

· Experience with AWS services, cloud-native deployment, queues, event-driven workflows, and data pipelines.

· Experience with Python frameworks such as FastAPI, Java frameworks such as Spring Boot, or Node.js/TypeScript API development.

· Experience with hybrid search, embeddings, automated chunking, retrieval workflows, or search-driven AI systems is a plus.