Decagon

Research Engineer role focused on building and evolving agent harnesses, runtime systems, and orchestration layers for a conversational AI platform. The role involves designing and implementing systems for routing, execution, tool invocation, and safety guarantees, with a strong emphasis on optimizing for latency, reliability, and production correctness through experimentation and analysis of real-world failures. The position operates in a fast-moving, ambiguous environment, requiring collaboration with Research, Infra, and Product teams.

Research Engineer role focused on building and evolving agent harnesses, runtime systems, and control-plane logic for a conversational AI platform. The role involves designing distributed systems for agent orchestration, optimizing for latency and reliability, and iterating based on real-world failures and experimentation. It operates in a fast-moving, ambiguous space with tight feedback loops, collaborating with Research, Infra, and Product teams.

Staff Research Engineer at Decagon, a conversational AI platform company. The role focuses on building and deploying industry-leading conversational AI models and agents for enterprise customer experiences. Responsibilities include leading research and engineering for core conversational capabilities, building end-to-end models and pipelines, and integrating them into production systems. Requires experience in post-training and deploying LLMs, Python, ML tooling, and a track record of delivering production impact from research ideas.

Senior Research Engineer at Decagon, a conversational AI platform company. The role focuses on building and deploying industry-leading conversational AI models and agents, from idea to production. Responsibilities include improving core conversational capabilities, building end-to-end models and pipelines, and integrating new models into production systems. Requires 5+ years of AI/ML experience, prior experience post-training and deploying LLMs in production, and fluency in Python and ML tooling.

Staff Software Engineer to design and build the runtime and model orchestration layer for conversational AI agents. This role focuses on the agent harness, including routing, execution logic, tool orchestration, and control-plane systems to ensure reliable, low-latency, and delightful user experiences across various channels. The position involves optimizing for latency, reliability, and production correctness, analyzing failures, building feedback loops, and adapting systems as model capabilities evolve.

Senior Software Engineer to design and build the runtime and model orchestration layer for conversational AI agents. This role focuses on the agent harness, which handles routing, execution logic, tool orchestration, and control-plane systems for live conversations. The work involves optimizing for latency and reliability, analyzing failures, and iterating quickly to improve agent performance in production.

Engineering Manager to lead the Agent Orchestration team, responsible for the core execution layer of Decagon's conversational AI platform. This role involves building and leading a team, owning the technical strategy for the orchestration engine, driving architecture for complex reasoning and action flows, and ensuring reliability, testing, and observability. The focus is on coordinating model reasoning, tool use, and evaluation in production to enable predictable, safe, and scalable agent behavior.

Staff Research Engineer at Decagon, a conversational AI platform company. The role focuses on building and deploying industry-leading conversational AI models and agents, from idea to production. Responsibilities include improving core conversational capabilities, building end-to-end models and pipelines, and mentoring other researchers. Requires 8+ years of experience in AI/ML, prior experience post-training and deploying LLMs, and a track record of production impact.

Staff Software Engineer to design and build the runtime and model orchestration layer for Decagon's conversational AI platform. This role focuses on the agent harness, which handles routing, execution logic, tool orchestration, and control-plane systems for reliable, low-latency agent behavior in production. The work involves building distributed systems, optimizing for performance and reliability, and iterating based on real-world failures and experimentation.

The Agent Orchestration team builds the runtime and model orchestration layer that powers Decagon's agents in production. This role focuses on designing and building systems that govern how Decagon agents operate in real-world environments, including execution frameworks, model orchestration logic, and experimentation platforms to ensure agents are fast, reliable, and continuously improving. The work involves optimizing for latency, reliability, and production correctness, analyzing failures, and improving observability and testing systems.

Senior Research Engineer at Decagon, a conversational AI platform company. The role focuses on building and deploying industry-leading conversational AI models and agents, from idea to production. Responsibilities include improving core conversational capabilities (instruction following, retrieval, memory, long-horizon task completion), building end-to-end models and pipelines, and integrating new models into production systems. Requires 5+ years of AI/ML experience, prior experience post-training and deploying LLMs in production, and a track record of delivering measurable production impact from research ideas.

Senior Software Engineer to build and ship AI agents for customer interactions on a conversational AI platform. The role involves designing and building agents that outperform human agents, identifying trends to guide platform evolution, and experimenting with/integrating text and voice models at scale for large enterprise customers.

Decagon is seeking a Senior Software Engineer to join their Agent Engineering team. This role focuses on building and shipping AI agents that manage complex customer interactions across voice and chat channels for enterprise clients. The engineer will have end-to-end ownership, identify trends to guide platform development, and experiment with/integrate latest text and voice models at scale.

Customer Engineer, Agent Builder role focused on end-to-end execution of AI agent builds for enterprise customers, including configuration, integration, and validation of guardrails. Requires strong technical skills, customer interaction, and experience with LLM/AI agent development.

Staff Software Engineer, Voice Agent at Decagon, focusing on the architecture and evolution of the real-time voice platform for conversational AI customer experiences. The role involves leading projects to improve speech understanding, synthesis quality, timing, responsiveness, and reliability across millions of interactions, collaborating with Research, Infra, and Product teams. Responsibilities include defining standards for reliability, testing, and observability, building debugging frameworks, and mentoring senior engineers.

This role focuses on building AI automation agents and intelligent solutions to improve company efficiency and effectiveness. The engineer will design and deploy agents for sales processes, growth marketing, and post-sales support, as well as build an account mapping platform using scrapers, search APIs, and LLMs. The role also involves driving an AI-native culture, identifying internal champions, and defining best practices. Success will be measured by data on hours saved and additional work delivered, with a focus on internal stakeholder satisfaction.

Senior Software Engineer on the Enterprise Product team at Decagon, a conversational AI platform company. This role focuses on building self-serve tools and platforms for customers to create, configure, train, and optimize AI agents for customer experiences. The engineer will translate complex AI capabilities into intuitive interfaces for both technical and non-technical users, owning features end-to-end.

Director of Field Engineering leading technical delivery of AI agent deployments for enterprise customers, building teams and playbooks to scale. This role involves hands-on execution, customer engagement, and influencing the platform roadmap.