Senior Backend Software Engineer (AI Agent Runtime)

• Build real-time AI agent infrastructure: Design and operate the stateful, low-latency runtime that powers voice and chat AI agents — from LLM streaming and conversation state management to graceful recovery and multi-channel support
• Solve distributed systems problems: Own session management across scaled-out workers — including affinity, checkpointing, crash recovery, and consistency under concurrent access
• Build a function execution platform: Own a serverless-style runtime where customers deploy custom logic — build orchestration, container lifecycle, autoscaling, and versioned rollouts
• Own developer experience and test infrastructure: Build CLI tools, local development environments, and test execution frameworks that let engineers iterate quickly and ship with confidence
• Raise the bar on production quality: Drive observability, incident response, and engineering best practices across the team

Benefits

• Weekly lunch & learn
• Work with an A+ team of ex-Founders, world leading scientists, and nationally competitive athletes
• Mentorship - A world class mentorship board advises and mentors our team-members to capture the opportunity ahead of us

• 5+ years of software engineering experience, with meaningful time spent on infrastructure, platform, or systems work
• Comfort operating what you build — on-call, incident response, and production ownership
• Experience with Kubernetes and cloud-native infrastructure
• Strong communicator who can drive technical decisions, write clear design docs, and mentor others
• AI-native workflow — you actively use LLMs and AI-assisted tools in your daily development, and can leverage them to move faster and tackle problems that would otherwise be impractical
• Deep understanding of distributed systems: consistency, fault tolerance, state management, concurrency
• Experience building developer-facing tooling — CLIs, SDKs, local dev environments, or internal platforms
• High bar for code quality — thorough testing, thoughtful code review, and sustainable engineering practices
• Strong Python and Go — both are core to this role, not one primary and one secondary
• Experience with real-time voice or streaming media systems
• Hands-on with LLM integration — streaming inference, prompt orchestration, retrieval-augmented generation
• Experience building serverless or function-as-a-service platforms
• Workflow engines (Temporal, Argo, Airflow) for durable, long-running processes
• Experience in conversational AI or speech domains
• Infrastructure-as-code and GitOps workflows