Search Engineer

We are seeking an experienced Search Engineer with strong hands-on expertise in Apache Solr and/or OpenSearch, Java, Python, Linux, and AWS. The ideal candidate will have experience administering and optimizing production search clusters, troubleshooting distributed systems, implementing infrastructure automation, and improving application development efficiency using AI-assisted tools.

Key Responsibilities

• Administer, configure, and maintain Apache Solr and OpenSearch clusters in production environments.

• Monitor search infrastructure performance, troubleshoot issues, and optimize indexing and query execution.

• Manage distributed search systems, including sharding, replication, cluster topology, and consistency.

• Develop, debug, and modify existing application code using Java and Python.

• Configure and manage AWS services, including EC2, IAM, VPC, S3, and CloudWatch.

• Support search infrastructure hosted on third-party cloud platforms such as Google Cloud Platform (Google Cloud Platform).

• Work with REST APIs, Query DSL, index management, and lifecycle policies such as ILM and ISM.

• Implement and maintain CI/CD pipelines and Infrastructure-as-Code solutions using Terraform, Ansible, CloudFormation, or similar tools.

• Work with Docker and Kubernetes for containerization and orchestration.

• Implement monitoring and observability using Prometheus, Grafana, CloudWatch, or similar tools.

• Use AI-assisted development tools such as Claude and GitHub Copilot to improve productivity and code quality.

• Follow Git-based version control practices, code reviews, and established engineering standards.

Required Qualifications

• 4+ years of hands-on experience administering Solr and/or OpenSearch in production environments.

• 5–10 years of experience with AWS, Java, Linux, and Python.

• 2–5 years of experience with Apache Solr and OpenSearch.

• Strong programming skills in Java and Python, including debugging and modifying existing code.

• Solid understanding of distributed systems, sharding, replication, consistency, and cluster topology.

• Hands-on experience with AWS services, including EC2, IAM, VPC, S3, and CloudWatch.

• Experience managing clusters on at least one non-AWS cloud platform, such as Google Cloud Platform.

• Knowledge of REST APIs, Query DSL, and index lifecycle management policies.

• Experience with CI/CD, Infrastructure-as-Code, Docker, and Kubernetes.

• Strong troubleshooting, debugging, and performance-tuning skills.

• Familiarity with monitoring, observability, Git, and code review workflows.

• Practical experience with AI-assisted development tools such as Claude or GitHub Copilot.