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# Senior Software Engineer - Microservices

- **Company:** Hume AI
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $150,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Databases, Continuous Integration, Data Stores, Software Debugging, Linux, Distributed Systems, Memory Management, Amazon DynamoDB, HAProxy, PostgreSQL, Machine Learning, Network Protocols, Nginx, Prometheus, Transmission Control Protocol (TCP), WebSocket, Openapi, Datadog, Google Cloud, Audio Streaming, Backend, Kubernetes, Low Latency, Dynatrace, Microservices
- **Published:** September 2, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b8fd7e25c10d8491

## About the Role

* A deep understanding of networking protocols and concepts, including TCP, TLS, HTTP, and WebSocket.
 * Professional experience with at least one systems-oriented programming language, such as Rust, Go, C, or C++.
 * Strong Linux fundamentals and hands-on experience troubleshooting and profiling production systems.
 * Experience with one or more relevant systems areas, such as distributed systems, networking, concurrency, resource management, filesystems, or computer architecture.
 * Experience designing, operating, and evolving production APIs and backend services.
 * Experience with testing frameworks and CI/CD workflows.
 * Experience with databases such as PostgreSQL, DynamoDB, or Google Cloud Datastore.
 * A strong sense of ownership and the ability to make pragmatic engineering and architectural decisions independently.
 * Excellent written and verbal communication skills. Engineers at Hume document the systems and products they build.
 * The ability to use AI-assisted coding tools effectively to accelerate delivery while retaining ownership of the result-including the ability to explain, validate, debug, and modify the resulting code independently when necessary.

Bonus Points

 * Demonstrated experience designing or building high-concurrency, high-throughput, or latency-sensitive systems.
 * Experience designing or operating control plane/data plane architectures.
 * Experience with Kubernetes.
 * Experience with observability and distributed tracing tools such as Datadog, Prometheus, or OpenTelemetry.
 * Experience with L4/L7 proxies such as NGINX, HAProxy, or Envoy.
 * Experience designing REST or gRPC APIs and OpenAPI specs.
 * Experience building container images and maintaining production CI/CD pipelines.

## Description

As a Senior Software Engineer on the Backend Engineering team, you will help build the backend microservices that power Hume's APIs and control planes. You will work closely with data plane engineers, UI engineers, research scientists, machine learning engineers, product managers, and infrastructure engineers to bring new product features and inference capabilities into production.

This is a systems-oriented backend role focused on reliability, performance, scalability, and efficient resource utilization. You will operate with a high degree of autonomy, make sound architectural decisions, and own systems throughout their lifecycle-from initial design and implementation through deployment, observability, and production support.

What You'll Do

 * Design, build, and maintain the backend microservices that deliver Hume's voice AI capabilities to users.
 * Design and develop public-facing and internal APIs that are secure, reliable, performant, and highly available.
 * Diagnose complex production issues across application, operating system, container, and networking layers.
 * Build capabilities such as real-time audio streaming and integrations with model inference systems.
 * Design and develop control plane APIs that coordinate inference workloads across data planes.
 * Profile and optimize latency, throughput, memory usage, and resource utilization.
 * Improve the observability, resilience, testability, and operational safety of the platform.
 * Make architectural and implementation tradeoffs across reliability, performance, complexity, and development velocity.
 * Collaborate with research and product teams to turn emerging model capabilities into reliable production systems.
 * Write clear technical documentation for the systems and features you build.