• Lead teams responsible for core systems powering member experience • Build, scale, and mentor high-performing engineering teams • Ensure backend services are scalable and trustworthy

• You will architect and launch backend and data systems that serve as the foundation of the company’s core product. • You will enable reliable ingestion and processing of large-scale external data sources, ensuring high availability and data quality. • You will help unlock intelligent search, discovery, and AI-driven features through scalable indexing and vector systems. • You will improve engineering efficiency, reliability, and cost control through strong infrastructure, observability, and automation practices. • You will directly influence the company’s ability to scale product features, onboard data partners, and deliver AI-powered user experiences. • Architect and provision secure cloud environments, including networking, IAM, and security best practices. • Implement Infrastructure-as-Code using tools such as Terraform or Pulumi. • Establish standards for secrets management, cost optimization, and observability. • Design scalable backend services to support core product functionality. • Design and build robust integrations with third-party APIs and external systems. • Develop resilient, idempotent ingestion pipelines capable of handling large-scale data volumes. • Implement schema management, data validation, and fault-tolerant ingestion workflows. • Maintain reliable data synchronization across multiple sources. • Build and maintain ETL/ELT pipelines using modern orchestration tools. • Implement transformation workflows using dbt and manage CI/CD pipelines for backend and data services. • Develop automated testing, monitoring, and alerting to ensure data quality and system reliability. • Provision and scale distributed search platforms such as Elasticsearch or OpenSearch. • Deploy and manage vector databases, including backups, scaling, and upgrades. • Optimize indexing strategies for fast, intelligent retrieval across large datasets. • Build backend pipelines for generating and managing embeddings using modern ML models. • Support Retrieval-Augmented Generation (RAG) systems using industry-standard frameworks. • Collaborate with product and AI teams to enable scalable, production-ready AI features.

• Leading the design and delivery of complex backend features and services, from concept through deployment and maintenance • Developing high-quality, production-grade software using Java and Spring Boot, aligned with architectural standards • Driving technical excellence by applying best practices, clean architecture principles, and robust testing strategies • Mentoring junior and mid-level engineers through code reviews, pair programming, and design guidance • Improving automation, reliability, performance, and overall engineering practices within the team • Collaborating closely with product, delivery, and engineering teams to shape effective technical solutions • Contributing to technical strategy and influencing patterns, standards, and long-term scalability.

• Designing, developing, and maintaining production-grade backend software in Java • Delivering end-to-end features: from requirements analysis and design, through implementation, testing, deployment, and maintenance • Working closely with engineering, product, and delivery teams to align technical solutions with business goals • Participating in code reviews, pair programming, and knowledge sharing within the team • Contributing to CI/CD pipelines, automated testing, and DevOps practices to improve delivery efficiency • Continuously improving code quality, reliability, and maintainability of the system