Job Summary

You’ll be a staff-level backend engineer who builds and operates the services that power our core product experiences. This is a hands-on role focused on designing reliable APIs and event-driven systems, writing and reviewing production code, and improving performance and scalability over time. 

Key Responsibilities

You Will:

• Design, build, and maintain backend services and APIs that are secure, scalable, and easy to evolve

• Deliver complex projects end-to-end (technical design, implementation, testing, rollout, and iteration based on real production feedback)

• Build event-driven and asynchronous workflows using Kafka and queue-based systems to improve resilience and throughput

• Own service reliability: monitoring, logging, alerting, incident response, and post-incident improvements

• Partner with Infrastructure/SRE to build and operate systems on AWS (compute, networking, storage, and deployment patterns)

• Define and improve data access patterns across SQL and NoSQL databases, including migrations and performance tuning

• Implement caching strategies (e.g., Redis/Memcached) to reduce latency, protect dependencies, and manage load

• Raise code quality through reviews, documentation, and setting practical standards for testing and operational readiness

Skill Requirements

• 10+ years of backend engineering experience building and operating production systems

• Strong fundamentals in system design, API design, data modeling, and writing maintainable, well-tested code

• Experience working in AWS and understanding common infrastructure components (e.g., VPC/networking concepts, compute, storage, managed services)

• Strong experience with SQL databases (e.g., Postgres/MySQL) and NoSQL systems (e.g., DynamoDB/MongoDB/Cassandra)

• Hands-on experience with Kafka and message/queue systems (e.g., SQS/RabbitMQ), including delivery semantics and failure handling

• Practical knowledge of caching patterns and cache invalidation strategies using tools like Redis or Memcached

• Strong observability practices, including structured logging, metrics, tracing, and familiarity with logging/monitoring tools

• A degree in Computer Science/Engineering or equivalent practical experience

Other Requirements

• Knowledge of Decentralized Identity (DCI) and Identity & Access Management (IAM) concepts, including auth patterns like OAuth/OIDC

• Experience with DataLake and Spark for large-scale ETL, batch processing, or analytics pipelines

• Experience with privacy/security best practices (PII handling, encryption, retention policies, audit logging)

• Experience scaling systems with cost and performance constraints (capacity planning, load testing, bottleneck analysis)