Senior Software Engineer, Backend (AI Agent Runtime)

Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day.

Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.

Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta.

About the role

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.

What we’re looking for

5+ years of software engineering experience, with meaningful time spent on infrastructure, platform, or systems work.

Strong Python and Go — both are core to this role, not one primary and one secondary.

Deep understanding of distributed systems : consistency, fault tolerance, state management, concurrency.

Experience with Kubernetes and cloud-native infrastructure.

Experience building developer-facing tooling — CLIs, SDKs, local dev environments, or internal platforms.

Strong communicator who can drive technical decisions, write clear design docs, and mentor others.

High bar for code quality — thorough testing, thoughtful code review, and sustainable engineering practices.

Comfort operating what you build — on-call, incident response, and production ownership.

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.

Nice-to-haves

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.