[Remote] Sr Software Engineer - Playlist

Note: The job is a remote job and is open to candidates in USA. Playlist is building a platform for intentional living that connects people with experiences in fitness, wellness, and beyond. The company is seeking a senior, hands-on backend engineer to design, build, and operate reliable backend services and APIs at scale, with a strong focus on distributed systems, data modeling, engineering excellence, and using AI tooling to accelerate delivery and improve quality.

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
• Additional responsibilities may be assigned as needed to support the team and business goals

Skills

• 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
• 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
• AI-native builder mindset with strong judgment; understanding of AI tooling such as MCPs, evals, RAG are good to have

Benefits

• A performance bonus
• Other applicable incentive compensation plans

Company Overview

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