Backend Engineer

Backend Software Engineer

Summary

A backend software engineer for Search is a software engineer focused on the API, algorithms, and cloud backend that contribute to an e-
commerce search engine user’s experience.

Education
Bachelor's Degree in Computer Science, Software Engineering
Advanced Degree (Master's or PhD) in Computer Science, Information Retrieval, Natural Language Processing, or Machine Learning is
beneficial, especially if they’ll be involved in developing custom search or ranking algorithms.

Skills
Programming languages
Ideally proficient in Kotlin, JVM, Java Class Library for backend development. Other backend development experience such with as
Node.js or Python will be considered.
Familiarity with Go or Rust for high-performance requirements might be a plus.
Search engine technology
Strong experience with OpenSearch, ElasticSearch, and possibly Solr, or Algolia for indexing and retrieving search data.
Familiarity with query optimization, indexing strategies, and search relevance tuning.
Knowledge of vector search and embedding-based search for personalized or semantic search is beneficial.
Data storage and management
Proficiency with databases (both SQL and NoSQL), such as PostgreSQL, MySQL, MongoDB, or DynamoDB.
Knowledge of caching solutions like Redis or Memcached to improve search response times.
Understanding of data pipelines and ETL processes to ingest and process product or user data in near-real-time.
Algorithm Development
Experience developing and implementing search algorithms for ranking, relevance scoring, and personalization.
Knowledge of machine learning for search (e.g., natural language processing, embeddings) is advantageous, especially if working
with personalized or semantic search features.
APIs and microservices
Ability to design, develop, and optimize RESTful APIs or GraphQL for handling search requests and responses.
Experience with microservices architecture and the ability to break down the search service into scalable, manageable components.
Performance optimization
Strong focus on performance and scalability to handle large numbers of search queries and rapid response times.
Proficiency in monitoring tools (e.g., Prometheus, Grafana) and log analysis to identify performance bottlenecks.
Security and reliability
Understanding of API security best practices, such as authentication, rate-limiting, and data protection.
Experience with distributed systems to ensure high availability and fault tolerance of the search engine.
Version control and CI/CD
Proficient in Git for version control.
Familiar with CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI) to automate testing and deployment pipelines.

Responsibilities
Building and maintaining the search backend
Develop and maintain the backend search engine and ensure it meets high standards of reliability and performance.
Implement search-related backend features like indexing, filtering, faceting, and ranking algorithms, both inside a third-party search
engine and outside one (in custom code using efficient data structures and algorithms and possibly natural language processing and
information retrieval techniques).
Optimizing search relevance and ranking
Adjust search relevance and ranking algorithms to improve search result quality, considering factors like user engagement and
conversion.
Collaborate with data scientists to experiment with and deploy ranking signals or personalization.
Performance optimization and scaling
Optimize the search infrastructure to handle a growing number of products and users with low latency.
Implement caching and load balancing to ensure fast and consistent search responses.
Data integration and management
Set up and maintain data pipelines for product information, user behavior, and search logs to keep search indices updated in real
time.
Work with database and data engineering teams to ensure that data is structured and stored efficiently for rapid access.
API development and maintenance
Design and maintain APIs for the frontend team to access search results, facets, and filters.
Ensure APIs are secure, scalable, and documented, facilitating easy integration by frontend engineers.
Monitoring and troubleshooting
Implement monitoring and alerting for search service performance and availability.
Identify and resolve issues that affect search quality or uptime, such as data indexing problems or server latency.
Continuous improvement & experimentation
Participate in A/B tests or experiments to improve search algorithms and evaluate user engagement with search features.
Keep up-to-date with advancements in search technology, machine learning, and NLP that can enhance the search experience.
Collaboration and knowledge sharing
Work closely with frontend, product, and UX teams to align on search functionality and user experience goals.

Current Technologies
We currently use the following technologies in backend engineering
Kotlin
Kotlin Coroutines
Spring Boot
GraphQL/DGS Framework
Opensearch
MongoDB
Mysql/MariaDB
gRPC/Protobuf
RabbitMQ
Kafka (optional)
Redis
Junit/Testcontainers/Mockk
AWS

Helm
Argo CD
Kubernetes
Grafana/Prometheus
Disturbed tracing - Opentelemetry
Sentry
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