Decagon currently has 42 active AI-related job listings. The majority of these roles, 88%, are focused on agents, with a smaller number in serving infrastructure and post-training. Engineering is the dominant function, with 32 positions, followed by product roles. The company is actively hiring in the United States and the United Kingdom. Recent hiring trends show a significant increase, with 16 new AI roles posted in the last 30 days, a 433% rise compared to the previous 30-day period.
Currently tracking 36 active AI roles, up 118% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $150k–$430k (avg $281k).
Decagon currently has 43 active AI-related roles in our index. The most common open titles are: Senior Agent Product Manager (4), Customer Engineer, Agent Builder - Spanish Speaking (3), Engineering Lead, Strategic Deals (2), Engineering Manager, Agents (2), Senior Research Engineer (2). Most positions are in Engineering and Product.
Decagon's active AI hiring is concentrated in: agents (88%), serving infrastructure (5%), post-training (5%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Decagon is hiring AI talent in: United States (33 roles), United Kingdom (6 roles), Germany (1 role), Canada (1 role).
Job postings at Decagon most frequently mention: Agentic Systems, Planning & Reasoning, System Design, Machine Learning, A/B Testing.
In the past 30 days, Decagon has posted 16 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Senior Software Engineer, Cloud Infrastructure Senior Software Engineer focused on building and operating the cloud infrastructure, ML serving, and deployment platforms for a conversational AI company. The role involves owning enterprise deployments in customer-owned cloud environments, ensuring reliability, scalability, and security of agentic AI workloads. | ServeAgent | 5 |
| Senior Software Engineer, Data Infrastructure Senior Software Engineer, Data Infrastructure role focused on building and operating data systems that power AI products. This involves designing and implementing high-throughput data pipelines, streaming systems, and analytical data layers, with a strong emphasis on reliability, performance, and scalability. The role partners with research and product teams to architect data solutions and optimize data paths for low latency. |
| Serve |
| 5 |