Playlist is a company focused on intentional living, connecting individuals with inspiring experiences in fitness and wellness. They are seeking a Senior Software Engineer to build and operate backend systems, focusing on distributed systems and data modeling while leveraging AI to enhance delivery and system capabilities.
Responsibilities:
- Partner with Product and Design to deliver features from ideation through deployment, iterating based on feedback and outcomes
- Design and ship backend services and APIs end-to-end, owning system design and architecture decisions across service boundaries, data ownership, consistency models, failure modes, and others
- Model and store data thoughtfully: schema design, indexing/partitioning, migrations, and performance tuning
- Promote engineering excellence by driving simplicity, strengthening operational health, and upholding quality through automated testing, code reviews, and monitoring/observability
- Mentor teammates and raise the bar for engineering rigor and clarity, including best practices for responsible AI usage
Requirements:
- 8+ years building and operating backend systems for high-traffic and high-reliability products
- Strong system design skills across distributed systems (latency, throughput, durability, backpressure, idempotency, retries, timeouts)
- Deep understanding of data modeling and persistence (relational and/or NoSQL), including tradeoffs around normalization, transactions, and consistency
- Experience designing service-oriented architectures (microservices or modular monoliths), including service-to-service communication patterns
- Solid CS fundamentals and engineering judgment, proficiency in an OO language (e.g., Java/Kotlin/C#), and a solid understanding of SDLC and Agile methodologies
- AI-native builder mindset with strong judgment; understanding of AI tooling such as MCPs, evals, RAG are good to have
- Strong communication and collaboration across functions
- Languages and Frameworks: Java/Kotlin/C#, SpringBoot/NetCore. async/concurrency, RPC/REST
- Data: PostgreSQL/MongoDB/DynamoDB, Redis, schema migrations, indexing, partitioning/sharding
- Runtime & tooling: gradle, monorepos, CI/CD
- Testing: unit/integration/e2e testing (JUnit/Mockito/TestContainers)
- Observability: metrics/logging/tracing; New Relic/Datadog/Kibana/Grafana
- AI tooling: Claude Code/ Cursor/ Codex-style coding assistants; MCPs; agent/orchestration frameworks; safety harnesses
- Engineering Practices: automated testing, code reviews, CI/CD, observability, on-call, incident management — with AI-accelerated workflows where appropriate