Staff Software Engineer

Staff Software Engineer, Backend

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. You’ll work closely with Product, Data, Infrastructure/SRE, and Security to deliver well-scoped solutions that are safe to run in production. You’ll also help strengthen backend engineering practices through design reviews, mentoring, and thoughtful technical guidance. You’ll report to an engineering manager and collaborate with peers to align backend work with broader platform goals.

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

You Have:

10+ years of backend engineering (Java & Springboot) 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

Bonus Points If You Have:

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)