[Remote] Data & Storage Systems Engineer ($200K–$270K + competitive equity) AI-Native CRM Data Platform

Note: The job is a remote job and is open to candidates in USA. CoffeeSpace is a Sequoia-backed Series A AI startup focused on building an AI-native CRM. They are looking for a Data & Storage Systems Engineer to own core parts of their data platform, focusing on ingestion, storage, and serving systems, while also ensuring a better customer experience through architectural decisions.

Responsibilities

• Own meaningful parts of the data platform end to end across ingestion, storage, and serving systems
• Evolve core transactional and OLTP storage systems to support significantly higher throughput, stronger reliability, and more flexible data access patterns
• Build and operate distributed app-storage and serving systems using technologies such as TypeScript, Node.js, Kotlin, Rust, Aurora Postgres, FoundationDB, Cassandra, Vitess, DynamoDB-style systems, and related infrastructure
• Design high-leverage platform APIs and SDKs that pull common data access patterns out of application code and accelerate the rest of the engineering team
• Build stream processing pipelines for new data sources and support Kafka-based systems where they connect to core storage and serving needs
• Improve operational excellence by removing failure modes, investing in deployment automation, supporting zero-downtime migrations, and making pager ownership uneventful without a dedicated SRE team
• Help expand the platform to support new customer segments and use cases, including finer-grained permissions, new data types, new ingestion sources, and more advanced indexing and retrieval patterns
• Use AI tools as part of your engineering workflow, delegating implementation details where useful so you can spend more energy on architecture, design, and creative problem-solving

Skills

• 4+ years of backend or distributed systems engineering experience, with hands-on ownership of data-intensive systems at meaningful scale
• Built and operated transactional/OLTP app-storage or serving systems in production, using technologies such as DynamoDB, Aurora, Vitess, FoundationDB, Cassandra, or similar systems
• Strong in at least one backend language such as TypeScript/Node.js, Kotlin, Java, or Rust
• Experience with infrastructure-as-code and container orchestration, such as Terraform, Kubernetes, ECS, Docker, Pulumi, or similar tools
• Has worked in data-intensive environments with high throughput, reliability requirements, or complex migration challenges
• Product- and customer-oriented, with the ability to frame infrastructure decisions around business outcomes and user experience, not just technical purity
• Comfortable in a small, flat, high-ownership engineering team where there is no dedicated layer of process between you and the problem
• Ideally has startup experience during a hyper-growth phase, especially Series A through Series C
• Bonus points for exposure to OLAP, warehouse, search, or streaming systems such as Kafka, ClickHouse, Elasticsearch, Apache Iceberg, turbopuffer, or similar technologies

Benefits

• Competitive equity package with cash/equity tradeoff options
• Remote-first, US-based | Hubs in Boston, San Francisco, and Denver | Quarterly Boston team meetups
• Unmeasured time off
• A parent-friendly culture that values kindness alongside ambition

Company Overview