> Markdown version of [/jobs/ext/4617160-senior-software-engineer-agent-platform](https://www.wearedevelopers.com/jobs/ext/4617160-senior-software-engineer-agent-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Agent Platform - **Company:** DECAGON, LLC - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $250,000.0 - **Contract:** Permanent contract - **Skills:** Software Debugging, Distributed Systems, Python (Programming Language), TypeScript, Model-Driven Development, Multi-Agent Systems, Low Latency, Asynchronous Programming - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25304_e0abec4db2f872f0ca29927f273c9cdc ## About the Role * 5+ years of experience building production systems * Proficiency in Python or Typescript and comfort with asynchronous programming * Strong debugging skills across complex technical stacks * Ability to design reliable distributed systems that handle real-world failure modes * A track record of owning large technical projects end-to-end, * Experience with real-time or low latency systems * Experience with workflow engines, agents, or model-driven applications * Experience building tooling or infrastructure for other engineers * Experience with experimentation or evaluation systems ## Description The Agent Orchestration team builds the core execution layer that powers every agent interaction, coordinating model reasoning, evaluating agent behavior, and ensuring agents behave reliably in real customer environments. We focus on correctness, reliability, and speed, shaping how Decagon agents plan, decide, and act across millions of interactions., As a Senior Software Engineer on the Agent Orchestration team, you will design and build systems that determine how Decagon agents operate under real-world conditions. You will own complex distributed systems challenges and lay foundations that help teams improve agent performance, reliability, and quality., * Build the execution engine that powers intelligent agents at scale * Design systems that coordinate model reasoning and actions while staying fast and correct * Improve reliability through better testing, observability, and safeguards * Build foundations that help teams evaluate and improve agent behavior safely and continuously