Senior Software Engineer - Microservices

Hume AI is looking for a systems-oriented backend engineer to build the microservices, APIs, and control planes behind Hume’s voice AI platform. Join us in the heart of New York City and contribute to our endeavor to ensure that AI is guided by human values, the most pivotal challenge (and opportunity) of the 21st century.

About Us

Hume AI is a Series B startup dedicated to building artificial intelligence that is directly optimized for human well-being. As the first company to release speech language models, we’re focused on expanding our research to encompass audio understanding models and evaluation platforms for enterprises.

Our goal is to enable a future in which technology draws on an understanding of human emotional expression to better serve human goals. As part of our mission, we also conduct groundbreaking scientific research, publish in leading scientific journals like Nature, and support a non-profit, The Hume Initiative, that has released the first concrete ethical guidelines for empathic AI (www.thehumeinitiative.org). You can learn more about us on our website (https://hume.ai/) and read about us in WIRED, Forbes, and Venturebeat.

About the Role

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.

What You’ll Bring

• Significant professional experience building server-side, distributed, or systems software.

• 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.