Software Engineer

Acoustic Connect is a customer engagement platform built for modern lifecycle marketing, giving direct-to-consumer brands the Performance Edge to turn consumer intent into personalized messages across email, SMS, WhatsApp, mobile push, and web.

At the heart of it all is Audience - the team that manages millions of contacts across hundreds of customers. When brands trust us with their data, your code keeps that promise. You'll build the systems that ingest, validate, store, and serve contact data at scale. Fast. Accurate. Reliable. Because every feature we ship depends on it.

We're proud of the tools we use and invest in keeping them current:

Runtime & API: TypeScript, Node.js, AWS Lambda, GraphQL (Cosmo Federation)

Messaging & Data: Confluent Kafka, MongoDB Streams, MongoDB Atlas, Snowflake

Infrastructure & Operations: AWS, Terraform, Launch Darkly, Datadog

AI: Claude / Anthropic

• Build and maintain services that manage contact data at scale
• Design APIs and data pipelines that handle high-throughput ingestion and real-time updates
• Ensure data integrity across complex workflows—imports, deduplication, validation
• Write production TypeScript/Node.js code in a serverless AWS environment
• Work closely with product and platform teams to evolve our core data architecture
  
  

4+ years building production software, with solid experience in:

• TypeScript / Node.js — our primary stack
• AWS (Lambda or similar serverless patterns)
• GraphQL — we run a federated architecture with multiple subgraphs, so you should understand how graphs compose
• Message Services — understanding of event-driven architectures, stream processing concepts (Kafka, MongoDB Change Streams, or similar)

You care about data correctness, think in systems, and know that "it works" isn't the same as "it's reliable."

• Experience with MongoDB or Snowflake
• Background in SaaS, multi-tenant platforms, or customer data infrastructure
• Terraform and CI/CD experience (infrastructure as code, automated deployments)

• Take ownership of reliability—not just features
• Like solving hard data problems where scale matters
• Prefer small, autonomous teams over layers of process