You'll work on live audio systems: buffering, streaming, latency optimization, and the integration points with speech providers.
Conversation quality depends on how well we manage the LLM layer.
You'll work on the action framework: configurable API calls, success/failure branching, auth management and the runtime execution engine.
You'll work on how agents ingest, store, and retrieve knowledge at runtime.
Customers need to create, configure, test, and deploy voice agents easily and intuitively.
You'll help build evaluation frameworks for each model involved, post-call analytics, call quality metrics, and Datadog instrumentation.

Requirements

You have experience building production backend systems ideally in Python or Typescript (all levels welcome, 5+ years for senior roles).
You write async code naturally, understand how to design for performance and reliability, and have shipped systems that real users depend on.
You understand what makes real-time systems different from request/response API’s.
You've worked with LLMs or AI/ML systems in production.
You know evaluation matters and you've built or used tooling around it.
Event driven architectures, message queues, caching layers, and async task processing feel natural to you.
You've debugged distributed failures and designed systems that handle partial failures gracefully.
Testing strategy, observability, API design, and code review are things you do thoughtfully.
You communicate clearly.
You are familiar with AI coding tools and already embedded them into your day to day engineering processes.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonTypescriptasync programmingreal-time systemsLLMsAI/ML systemsevent driven architecturesmessage queuescaching layersasync task processing

Soft Skills

communicationdesign for performancedesign for reliabilitydebuggingsystem designtesting strategyobservabilityAPI designcode review