Job Opportunities API

About the Company: At Playlist, life's richest moments happen when people step away from screens to move, connect, explore, and play. We're building the definitive platform for intentional living, connecting people with inspiring experiences in fitness, wellness, and beyond. With popular brands like Mindbody and ClassPass, Playlist empowers businesses and individuals, making it effortless for aspirations to become actions. Join us in reshaping technology's role to foster meaningful, real-world connections. The Role You'll Play You’ll build and operate the backend systems that power Playlist. This is a senior, hands-on role focused on distributed systems, data modeling, and pragmatic system design—delivering reliable services at scale while keeping the architecture simple and maintainable. You’ll also operate at the edge of what’s possible by leveraging AI (LLMs and agentic tooling) to accelerate delivery, improve quality, and push system capabilities forward. 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  What We're Looking For 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 Tools and Systems You don’t need experience with every item below—what matters is strong fundamentals and the ability to learn quickly. 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   It is the Company’s intent to pay all Team Members competitive wages and salaries that are fair and equitable. Actual compensation packages are based on several factors unique to each candidate, including skill set, depth of experience, certifications, and work location. The goal of Company's compensation program is to be transparent, attract potential employees, meet the needs of all current employees, and encourage Team Members to stay with our organization. The base salary range for this position in the United State